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IMAQ Vision for LabVIEW User Manual

1. Kp Note If you have LabVIEW 7 0 or later you can use the property node and invoke node of the Image Display control to perform many of these ROI tasks ov Fa E National Instruments Corporation Image Manipulation A group of VIs that modify the spatial content of images Use these VIs to resample an image extract parts of an image and rotate shift and unwrap images This subpalette also contains VIs that copy images to and from the clipboard Pixel Manipulation A group of VIs that read and modify individual pixels in an image Use these VIs to read and set pixel values in an image or along a row or column in an image fill the pixels in an image with a particular value and convert an image to and from a 2D LabVIEW array Overlay A group of VIs that overlay graphics on an image display environment without altering the pixel values of the image Use these VIs to overlay the results of your inspection application onto the images you inspect Calibration A group of VIs that spatially calibrate an image to take accurate real world measurements regardless of camera perspective or lens distortion Use these VIs to set a simple calibration or to let IMAQ Vision automatically learn the calibration data from a grid image Then use the VIs to convert pixel coordinates to real world coordinates for simple measurements Color Utilities A group of VIs that access data from color images Use these VIs to extract different
2. Type the shape type of the contour e Coordinates An array containing the coordinates that define the contour e Specify regions by providing basic parameters that describe the region you want to define For example define a point by providing the x coordinate and y coordinate Define a line by specifying the start and end coordinates Define a rectangle by specifying the coordinates of the top left point bottom right point and the rotation angle in thousandths of degrees The Vision Utilities Region of Interest Region of Interest Conversion palette provides VIs to convert simple data types such as points lines rectangles and annuluses into an ROI descriptor Use the following VIs to convert an ROI contour encoded by a simple description to an ROI descriptor for that contour 4 e IMAQ Convert Point to ROI Converts a point specified by its x and y ROI coordinates E e IMAQ Convert Line to ROI Converts a line specified by its start and ROL end points e IMAQ Convert Rectangle to ROI Converts a rectangle specified by its top left and bottom right points and rotation angle e IMAQ Convert Annulus to ROI Converts an annulus specified by its center point inner and outer radii and start and end angles e IMAQ Convert Rectangle to ROI Polygon Converts a rectangle specified by its top left and bottom right points and rotation angle to an ROI descriptor that uses a polygon to represent the rectangle Use the fol
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4. Copyright Under the copyright laws this publication may not be reproduced or transmitted in any form electronic or mechanical including photocopying recording storing in an information retrieval system or translating in whole or in part without the prior written consent of National Instruments Corporation Trademarks CVI IMAQ LabVIEW National Instruments National Instruments Alliance Partner NI ni com NI Developer Zone and NI IMAQ are trademarks of National Instruments Corporation Product and company names mentioned herein are trademarks or trade names of their respective companies Members of the National Instruments Alliance Partner Program are business entities independent from National Instruments and have no agency partnership or joint venture relationship with National Instruments Patents For patents covering National Instruments products refer to the appropriate location Help Patents in your software the patents txt file on your CD or ni com patents WARNING REGARDING USE OF NATIONAL INSTRUMENTS PRODUCTS 1 NATIONAL INSTRUMENTS PRODUCTS ARE NOT DESIGNED WITH COMPONENTS AND TESTING FOR A LEVEL OF RELIABILITY SUITABLE FOR USE IN OR IN CONNECTION WITH SURGICAL IMPLANTS OR AS CRITICAL COMPONENTS IN ANY LIFE SUPPORT SYSTEMS WHOSE FAILURE TO PERFORM CAN REASONABLY BE EXPECTED TO CAUSE SIGNIFICANT INJURY TO A HUMAN 2 INANY APPLICATION INCLUDING THE ABOVE RELIABILITY OF OPERATION
5. Frequency Domain IMAQ Vision for LabVIEW User Manual 2 18 ni com Making Grayscale and Color Measurements This chapter describes how to take measurements from grayscale and color images You can make inspection decisions based on image statistics such as the mean intensity level in a region Based on the image statistics you can perform many machine vision inspection tasks on grayscale or color images such as detecting the presence or absence of components detecting flaws in parts and comparing a color component with a reference Figure 3 1 illustrates the basic steps involved in making grayscale and color measurements Define Regions of Interest Measure Measure Grayscale Statistics Color Statistics Figure 3 1 Steps for Taking Grayscale and Color Measurements Define Regions of Interest A region of interest ROTD is an area of an image in which you want to focus your image analysis Table 3 1 describes each of the ROI tools and the manner in which you use them You can define an ROI interactively programmatically or with an image mask National Instruments Corporation 3 1 IMAQ Vision for LabVIEW User Manual Chapter 3 Making Grayscale and Color Measurements Table 3 1 Tools Palette Functions Selection Tool Select an ROI in the image and adjust the position of its control points and contours Action Click ROI or control points Point Select a pixel in the image Action Click the position of th
6. Image Processing Figure 3 5 Primary Components of a 64 Bit Color Image ka ma Use the IMAQ ExtractSingleColorPlane VI or the IMAQ ExtractColorPlanes VI Vision Utilities Color Utilities to extract the red green blue hue saturation intensity luminance or value plane of a color image into an 8 bit image A color pixel encoded as an unsigned 32 bit integer control can be decomposed into its individual components using the IMAQ IntegerToColorValue VI You can convert a pixel value represented by its RGB components into the equivalent components for another color National Instruments Corporation 3 11 IMAQ Vision for LabVIEW User Manual Chapter 3 Making Grayscale and Color Measurements Comparing Colors model using the IMAQ RGBToColor 2 VI You can convert components in any other color mode to RGB by using the IMAQ ColorToRGB VI These three VIs appear in the Vision Utilities Color Utilities palette You can use the color matching capability of IMAQ Vision to compare or evaluate the color content of an image or regions in an image Complete the following steps to compare colors using color matching 1 Select an image containing the color information that you want to use as areference The color information can consist of multiple colors 2 Use the entire image or regions in the image to learn the color information using the IMAQ ColorLearn VI Image Processing Color Processing which outputs a color spectrum that con
7. but with more accurate results Data acquisition The process of collecting and measuring electrical signals from sensors transducers and test probes or fixtures and inputting them to a computer for processing A characteristic of a system that describes how consistently it can respond to external events or perform operations within a given time limit An image f x y that has been converted into a discrete number of pixels Both spatial coordinates and brightness are specified Increases the size of an object along its boundary and removes tiny holes in the object Software that controls a specific hardware device such as an IMAQ or DAQ device IMAQ Vision for LabVIEW User Manual G 4 ni com E edge edge contrast edge detection edge steepness energy center equalize function erosion exponential and gamma corrections exponential function FFT fiducial Fourier transform frequency filters ft function National Instruments Corporation G 5 Glossary Defined by a sharp transition in the pixel intensities in an image or along an array of pixels The difference between the average pixel intensity before the edge and the average pixel intensity after the edge Any of several techniques that identify the edges of objects in an image The number of pixels that corresponds to the slope or transition area of an edge The center of mass of a grayscale image See center of mass See histogram equ
8. or selecting the control and clicking Edit Customize Control During run time you can customize many parts of the control using property nodes Kp Note Not all functionality available during design time is available at run time To create a property node right click the control and select Create Property Node Click the Property Node once to see the properties you can configure Properties specific to the Image Display control appear at the end of the list The following list describes a subset of the properties available for the Image Display control e Snapshot Mode Determines if the control makes a copy of the image or has a reference to the image When you enable the Snapshot Mode if the inspection image changes later in your application the Image Display control continues to display the image as it was when the image was wired into the Image Display control Enabling the Snapshot Mode may reduce the speed of your application because the control makes a copy of the image Enable this property when you want to display a snapshot of the image in time Disable this property when you need to display results quickly such as during a grab acquisition The property is disabled by default Kp Note To cause the Image Display control to refresh the image immediately use the Refresh Image method To create a method right click the control and select Create Invoke Node Click the Invoke Node once to see the available methods Method
9. while a low score indicates a poor match The score can be used as a gauge to determine if a printed character is acceptable Use the Score element of the Matches indicator to get the score corresponding to a match Finding Points Using Color Pattern Matching Color pattern matching algorithms provide a quick way to locate objects when color is present Use color pattern matching if your images have the following qualities e The object you want to locate has color information that is very different from the background and you want to find a very precise location of the object in the image e The object to locate has grayscale properties that are very difficult to characterize or that are very similar to other objects in the search image In such cases grayscale pattern matching can give inaccurate results If the object has color information that differentiates it from the IMAQ Vision for LabVIEW User Manual 5 18 ni com Chapter 5 Performing Machine Vision Tasks other objects in the scene color provides the machine vision software with the additional information to locate the object Color pattern matching returns the location of the center of the template and the template orientation Complete the following general steps to find features in an image using color pattern matching 1 Define a reference or fiducial pattern in the form of a template image i 2 Use the reference pattern to train the color pattern matching algorithm
10. 5 10 Background Information Training the Pattern Matching Algorithm After you create a good template image the pattern matching algorithm has to learn the important features of the template Use IMAQ Learn Pattern 2 a to learn the template The learning process depends on the type of matching that you expect to perform If you do not expect the instance of the template in the image to rotate or change its size the pattern matching algorithm has to learn only those features from the template that are necessary for shift invariant matching However if you want to match the template at any orientation the learning process must consider the possibility of arbitrary orientations Use the IMAQ Setup Learn Pattern 2 VI Machine 8 Vision Searching and Matching to specify which type of learning mode to use a a The learning process is usually time intensive because the algorithm attempts to find unique features of the template that allow for fast accurate matching The learning mode you choose also affects the speed of the learning process Learning the template for shift invariant matching is faster than learning for rotation invariant matching You also can save time by training the pattern matching algorithm offline and then saving the RE template image with IMAQ Write Image and Vision Info VI Machine Vision Searching and Matching Defining a Search Area Two equally important factors define the success of a pattern matching a
11. An image file format for storing 8 bit and color images with lossy compression JPEG images have the file extension JPG A structure that represents a pixel and its relationship to its neighbors The relationship is specified by the weighted coefficients of each neighbor A morphology operation that identifies each object in a binary image and assigns a unique pixel value to all the pixels in an object This process is useful for identifying the number of objects in the image and giving each object a unique pixel intensity Laboratory Virtual Instrument Engineering Workbench A program development environment application based on the programming language G used commonly for test and measurement applications IMAQ Vision for LabVIEW User Manual Glossary line gauge line profile linear filter logarithmic function logic operators lossless compression lossy compression lowpass attenuation lowpass FFT filter lowpass filter lowpass frequency filter lowpass truncation L skeleton function luma Measures the distance between selected edges with high precision subpixel accuracy along a line in an image For example this function can be used to measure distances between points and edges This function also can step and repeat its measurements across the image Represents the gray level distribution along a line of pixels in an image A special algorithm that calculates the value of a pixel based on its own pixe
12. Ba with IMAQ Setup Learn Color Pattern 3 Define an image or an area of an image as the search area A small search area can reduce the time to find the features 4 Set the Feature Mode control to Color and Shape HP 5 Set the tolerances and parameters to specify how the algorithm Ba operates at run time using IMAQ Setup Match Color Pattern Ps 6 Test the search tool on test images using IMAQ Match Color Pattern ea Verify the results using a ranking method Defining and Creating Good Color Template Images The selection of a good template image plays a critical part in obtaining accurate results with the color pattern matching algorithm Because the template image represents the color and the pattern that you want to find make sure that all the important and unique characteristics of the pattern are well defined in the image Several factors are critical in creating a template image These critical factors include color information symmetry feature detail positional information and background information Refer to the Defining and Creating Good Template Images section of this chapter for more information about some of these factors Color Information A template with colors that are unique to the pattern provides better results than a template that contains many colors especially colors found in the background or other objects in the image Symmetry A rotationally symmetric template in the luminance plane is less sens
13. IMAQ AutoBThreshold VI Image Processing Processing to select the thresholding technique that automatically determines the optimal threshold range 2 Connect the Threshold Data output to the IMAQ MultiThreshold VI Image Processing Processing or use the Lookup Table output to apply a lookup table to the image using the IMAQ UserLookup VI Image Processing Processing If your grayscale image contains objects that have multiple discontinuous grayscale values use the IMAQ MultiThreshold VI Image Processing Processing Automatic thresholding techniques offer more flexibility than simple thresholds based on fixed ranges Because automatic thresholding techniques determine the threshold level according to the image histogram the operation is less affected by changes in the overall brightness and contrast of the image than a fixed threshold Because these techniques are more resistant to changes in lighting they are well suited for automated inspection tasks If you need to threshold a color image use the IMAQ ColorThreshold VI Image Processing Color Processing You must specify threshold ranges for each of the color planes either Red Green and Blue or Hue Saturation and Luminance The binary image resulting from a color threshold is an 8 bit binary image Improve the Binary Image After you threshold your image you may want to improve the resulting binary image with binary morphological functions You can use primary b
14. IMAQ provides the acquisition components and IMAQ Vision provides the image manipulation and analysis functions Develop your vision application with NI IMAQ and IMAQ Vision for LabVIEW Then download your code to run on a real time embedded target You also can add National Instruments data acquisition DAQ motion control contoller area network CAN and serial instruments to your LabVIEW RT system to create a complete integrated embedded system system Components Your Vision for LabVIEW RT system consists of a development system and one or more deployed RT targets Development System The Vision for LabVIEW Real Time Vision for LabVIEW RT development system is made up of the following major components e Host Pentium based machine running a Windows operating system Use this component to configure your PXI controller or NI CVS 1450 Series device as an RT target and to develop your application e RT target RT Series hardware that runs VIs downloaded from and built in LabVIEW Examples of RT targets include a National National Instruments Corporation A 1 IMAQ Vision for LabVIEW User Manual Appendix A Vision for LabVIEW Real Time Instruments PXI chassis housing a PXI controller and the NI 1450 Series Compact Vision System Refer to Appendix C NI IMAQ for LabVIEW Real Time of the NI IMAQ User Manual for details about how to set up each machine and how they interact with each other Kp Note You need a network
15. Image Dst which therefore receives the results from the operation In this operation the source data for Image Src A is overwritten In the pane on the right Image Src B receives the results from the operation and its source data is overwritten Most operations between two images require that the images have the same type and size However arithmetic operations can work between two different types of images Acquire or Read an Image After you create an image reference you can acquire an image into your imaging system in three ways You can acquire an image with a camera through your image acquisition device load an image from a file stored on your computer or convert the data stored in a 2D array to an image VIs that acquire images load images from file or convert data from a 2D array IMAQ Vision for LabVIEW User Manual 2 6 ni com Chapter 2 Getting Measurement Ready Images automatically allocate the memory space required to accommodate the image data Use one of the following methods to acquire images with a National Instruments IMAQ device snap e Acquire a single image using the IMAQ Snap VI Image Acquisition When you call this VI it initializes the IMAQ device and acquires the next incoming video frame Use this VI for single capture applications where ease of programming is essential f e Acquire images continually through a grab acquisition Grab functions setup perform an acquisition that loops continua
16. Items 2 and 3 in the last step in Figure 1 1 are expanded upon in Figure 1 2 You can use a combination of the items in the last step to create your IMAQ Vision application Refer to the corresponding chapter beside a figure item for more information about the item 1 6 ni com Chapter 1 Introduction to IMAQ Vision Set Up Your Imaging System Chapter 6 Calibrate Your Imaging System A Calibration Create an Image Acquire or Read an Image Chapter 2 Getting Measurement Ready Images Display an Image Attach Calibration Information Analyze an Image Improve an Image Make Measurements or Identify Objects in an Image Using O Grayscale or Color Measurements and or Particle Analysis and or G Machine Vision Figure 1 1 General Steps for Designing a Vision Application Kp Note Diagram items enclosed with dashed lines are optional steps National Instruments Corporation 1 7 IMAQ Vision for LabVIEW User Manual Chapter 1 Introduction to IMAQ Vision Chapter 3 Grayscale and Color Measurements Define Regions of Interest Measure Measure Grayscale Statistics Color Statistics Create a Binary Image Chapter 4 Particle Improve a Binary Image Set Search Areas Analysis Find Measurement Points Identify Parts Under Inspection i Make Particle Measurements Chapter 5 Classify Read Read Machine Objects Characters Barcodes Vision Convert Pixel Coordinates to Real World Coordinates Display Resul
17. LabVIEW User Manual Appendix A Vision for LabVIEW Real Time execution time may be particularly important Herein lies the need for time bounded algorithms Time Bounded Execution As with determinism time bounded behavior is controlled by both the algorithm and the environment in which it executes For this reason some vision algorithms are not candidates for time bounding For example algorithms whose execution time varies widely between similar images are not productive under time constraints This includes operations such as skeleton separation and segmentation whose execution time can vary dramatically with slight changes in the input image This makes choosing a time limit for such operations difficult However many vision algorithms are adaptable to time limits when the appropriate timed environment is established In Vision for LabVIEW RT the timed environment is best described in terms of the following process flow 1 Initialize the timed environment 2 Prepare resources 3 Perform time bounded vision operations 4 Close the timed environment Initializing the Timed Environment You must initialize the timed environment to manage resource allocation While LabVIEW RT manages all of the resources used by the vision application some resources must be allocated dynamically which leaves the possibility for resource contention For example if a vision algorithm needs to allocate memory for internal workspace it
18. Matching Algorithm ccccceeeeee 5 20 PEM MING a Seale hArainn a a aS 5 21 Setting Matching Parameters and Tolerances ccccceccccceeeeeeeees 5 22 Testing the Search Algorithm on Test Images cccccsscssseeeeeeees 5 24 Finding Points Using Color 0cavion cx svsesisesas sspastecenersindadaveduastlavdideenigauicadyes 5 25 Convert Pixel Coordinates to Real World Coordinates cccccceseeeeeneeenteeeeeeeees 5 25 Make Measure ICTS irienna ona a bas beroueces e En 5 26 Making Distance Measurements ssesssesesseeeeseeeeeeeeeseeseeseeeeeeeeeeeeeeeees 5 26 Making Analytic Geometry Measurements c cecssssessseeeseeeeseeeeeseesseeees 5 27 Making Instrument Reader Measurementts ssssesssssesseeeeeeeeseeeeseeees 5 27 Fdentity Parts Under Inspec OM sesei e an bea wabecnescenetoonabetsabacnasseneds 5 28 ClaSSIP IMS Samples rociis ei Na A 5 28 ISG AGING C Ab ACTE I sannana a eaa a R 5 29 RCAC Bal C OCG Susien a e e A AA 5 30 Reading ID Burci Sosanna aa a a a a 5 30 Reading Data Matrix Barcodes cccccccsccceseececceeeeeeeeeeeeeeasaeeaeaes 5 30 Reading PDF417 Bardes a aa 5 31 Display Kesu ea E r E E 5 31 National Instruments Corporation vii IMAQ Vision for LabVIEW User Manual Contents Chapter 6 Calibrating Images Perspective and Nonlinear Distortion Calibration cccccccssssessseeeeeeceeeeeeeeeeeeeeeees 6 1 Denna Calabria On Templat
19. ROI constructor The palette on the right displays the characteristics of the ROI you are drawing IMAQ Vision for LabVIEW User Manual 3 6 ni com Chapter 3 Making Grayscale and Color Measurements 203 134 Pixel Intensity o Bit Image o Bit Image Image type indicator 8 bit 16 bit Float Complex 32 bit RGB HSL 64 bit RGB Coordinates of the mouse on the active image window Anchoring coordinates of an ROI Size of an active ROI Length and horizontal angle of a line region Figure 3 3 Tools Palette Tools and Information Defining Regions Programmatically When you have an automated application you may need to define ROIs programmatically You can programmatically define regions in two ways National Instruments Corporation Specify the elements of an ROI descriptor which are described as follows Global rectangle Four integers that describe the bounding rectangle containing all of the shapes in the ROI descriptor Contours Each of the individual shapes that define an ROI as follows e ID Specifies if the contour is the external or internal edge of an ROI If the contour is external all of the area inside of it is considered part of the ROI Because external contours are calculated first internal contours override external contours giving you the ability to exclude regions inside external contours 3 7 IMAQ Vision for LabVIEW User Manual Chapter 3 Making Grayscale and Color Measurements e
20. ROIToMask VI Vision Utilities Region of Interest to z convert the ROI descriptor into an image mask a National Instruments Corporation 3 5 IMAQ Vision for LabVIEW User Manual Chapter 3 Making Grayscale and Color Measurements You also can use the IMAQ Select Point VI IMAQ Select Line VI and IMAQ Select Rectangle VI to define regions of interest These three VIs appear in the Machine Vision Select Region of Interest palette Complete the following steps to use these VIs Ce 1 Call the VI to display an image in an ROI Constructor window Only the tools specific to that VI are available for you to use 2 Select an ROI tool from the tools palette Draw an ROI on your image Resize or reposition the ROI until it covers the area you want to process 4 Click OK to output a simple description of the ROI You can use this description as an input for the VIs on the Machine Vision Intensities palette that measure grayscale intensity e IMAQ Light Meter Point Uses the output of IMAQ Select ji Point e IMAQ Light Meter Line Uses the output of IMAQ Select Line e IMAQ Light Meter Rect Uses the output of IMAQ Select Rectangle Tools Palette Transformation The tools palette shown in Figure 3 3 is a component of external display windows and ROI constructors The tools palette automatically transforms from the palette on the left to the palette on the right when you manipulate a region tool in a display window or
21. VI Image Processing Processing to label your image mask E E i _ E National Instruments Corporation 3 9 IMAQ Vision for LabVIEW User Manual Chapter 3 Making Grayscale and Color Measurements Use the IMAQ Centroid VI Image Processing Analysis to compute the energy center of the image or of a region within an image Measure Color Statistics Most image processing and analysis functions apply to 8 bit and 16 bit images However you can analyze and process individual components of a color image ma Using the IMAQ ExtractColorPlanes VI Vision Utilities Color Utilities you can break down a color image into various sets of primary components such as RGB Red Green and Blue HSI Hue Saturation and Intensity HSL Hue Saturation and Luminance or HSV Hue Saturation and Value Each component becomes an 8 bit or 16 bit image that you can process like any other grayscale image Using the wa IMAQ ReplaceColorPlane VI Vision Utilities Color Utilities you can reassemble a color image from a set of three 8 bit or 16 bit images where each image becomes one of the three primary components Figure 3 4 and Figure 3 5 illustrate how 32 bit and 64 bit color images break down into their three primary components IMAQ Vision for LabVIEW User Manual 3 10 ni com Chapter 3 Making Grayscale and Color Measurements 8 bit Image Processing Figure 3 4 Primary Components of a 32 Bit Color Image 16 bit
22. Vision Deployment Engine Note to Users If you need information about how to deploy your custom IMAQ Vision applications on target computers read this CD insert e Your National Instruments PXI controller user manual lIf you are using the LabVIEW Real Time Module to develop your vision application and need information about how to set up your PXI controller device in your PXI chassis refer to this manual e NI 1450 Series Compact Vision System Digital I O Help lItf you need information about configuring the NI 1450 digital I O and shutdown components as well as parameter reference information for each of the components refer to this help file e Example programs If you want examples of how to create specific LabVIEW applications launch the NI Example Finder from Help Find Examples within LabVIEW 6 1 and later National Instruments Corporation Xiii IMAQ Vision for LabVIEW User Manual About This Manual IMAQ Vision for LabVIEW User Manual Application Notes If you want to know more about advanced IMAQ Vision concepts and applications refer to the Application Notes located on the National Instruments Web site at ni com appnotes nsf NI Developer Zone NIDZ If you want even more information about developing your vision application visit the NI Developer Zone at ni com zone The NI Developer Zone contains example programs tutorials technical presentations the Instrument Driver Network a measurement glossary an on
23. Vision for LabVIEW User Manual Appendix A Vision for LabVIEW Real Time Troubleshooting This section describes solutions and suggestions for common errors in Vision for LabVIEW RT Remote Display Errors Why am I unable to display remote images using IMAQ WindDraw The Vision Remote Server controls the displaying of images acquired from your remote systems in external windows If you are unable to display your remote images press lt Ctrl Alt Del gt which opens the Windows Task Manager and confirm that NIVisSvr exe is running as an active process If NIVisSvr exe is not running close and restart LabVIEW RT and any open IMAQ Vision applications If you still experience errors contact National Instruments Technical Support Technical support information is available in Appendix B Technical Support and Professional Services Why does my remotely displayed image have low quality Try these steps to improve your image quality e Ensure that your camera aperture is open to allow the appropriate amount of light for an acquisition e Check your compression settings e Make sure that your display settings in Windows are set to use at least 24 bit color How do I select an ROI in an image If you are using LabVIEW RT 7 0 or later you can you use an Image Display control to select an ROI Wire your inspection image to the Image Display control on your LabVIEW block diagram to display the image on your LabVIEW front panel
24. Window Display Display an image in an external window using the IMAQ WindDraw VI z Vision Utilities Display You can display images in 16 different external m windows Use the IMAQ WindSetup VI Vision Utilities Display to z configure the appearance of each external window For example you can decide if the window has scroll bars is resizable or has a title bar You also can use the IMAQ WindMove VI Vision Utilities Display to position the a external image window at a particular location on the monitor Kp Note External image windows are not LabVIEW panels They are managed directly by IMAQ Vision IMAQ Vision for LabVIEW User Manual 2 8 ni com Chapter 2 Getting Measurement Ready Images You can use a color palette to display grayscale images by applying a color palette to the window You can use the IMAQ GetPalette VI Vision z Utilities Display to obtain predefined color palettes For example if you need to display a binary image an image containing particle regions with pixel values of 1 and a background region with pixel values of 0O apply the predefined binary palette Refer to Chapter 2 Display of the IMAQ Vision Concepts Manual for more information about color palettes Kp Note At the end of your application you must close all open external windows using the IMAQ WindClose VI Vision Utilities Display Image Display Control Use the Image Display control to display an image on the LabVIEW front g p
25. an image depends on both the template size and the search area By reducing the search area you can reduce the required search time Increasing the template size can improve the search time but doing so reduces match accuracy if the larger template includes an excess of background information Setting Matching Parameters and Tolerances Every color pattern matching algorithm makes assumptions about the images and color pattern matching parameters used in machine vision applications These assumptions work for a high percentage of the applications However there may be applications in which the assumptions used in the algorithm are not optimal In such cases you must modify the color pattern matching parameters Knowing your particular application and the images you want to process is useful in selecting the pattern matching parameters Use the IMAQ Setup Match Color Pattern VI IMAQ Vision for LabVIEW User Manual 5 22 ni com Chapter 5 Performing Machine Vision Tasks T Machine Vision Searching and Matching to set the following Ba parameters that influence color pattern matching color sensitivity search strategy color score weight ignore colors minimum contrast and rotation angle ranges Color Sensitivity Use the color sensitivity to control the granularity of the color information in the template image If the background and objects in the image contain colors that are very close to colors in the template image use a higher c
26. can configure which ROI tools are present on the control Complete the following steps to configure the ROI tools palette during design time 1 Right click the ROI tools palette and select Visible Items ROI Tool Button Visibility 2 Deselect the tools you do not want to appear in the ROI tools palette If you do not want any of the tools to appear click All Hidden 3 Click OK to implement the changes To get or set ROIs programmatically use the property node for the Image Display control Defining an ROI in an External Window The following list describes how you can display the tools palette in an external window and manipulate the palette You can find all the following VIs on the Vision Utilities Region of Interest palette e Use the IMAQ WindToolsShow VI to display the tools window in a floating window F Use the IMAQ WindToolsSetup VI to configure the appearance of the tools window e Use the IMAQ WindToolsMove VI to move the tools palette e Use the IMAQ WindToolsClose VI to close the tools palette ol pi EJ ba Kj Note If you want to draw an ROI without displaying the tools palette in an external Cot window use the IMAQ WindToolsSelect VI Vision Utilities Region of Interest This VI allows you to select a contour from the tools palette without opening the palette Defining an ROI Using an ROI Constructor The IMAQ ConstructROI VI enables you to incorporate into your application a LabVIEW modal window
27. denotes the messages and responses that the computer automatically prints to the screen This font also emphasizes lines of code that are different from the other examples National Instruments Corporation xi IMAQ Vision for LabVIEW User Manual About This Manual Related Documentation In addition to this manual the following documentation resources are available to help you create your vision application IMAQ Vision e IMAQ Vision Concepts Manual lIf you are new to machine vision and imaging read this manual to understand the concepts behind IMAQ Vision e IMAQ Vision for LabVIEW Help lf you need information about IMAQ Vision palettes or individual IMAQ Vision VIs while creating your application refer to this help file You can access this file by selecting Help IMAQ Vision from within LabVIEW NI Vision Assistant e NI Vision Assistant Tutorial If you need to install NI Vision Assistant and learn the fundamental features of the software follow the instructions in this tutorial e NI Vision Assistant Help lIf you need descriptions or step by step guidance about how to use any of the functions or features of NI Vision Assistant refer to this help file NI Vision Builder for Automated Inspection e NI Vision Builder for Automated Inspection Tutorial If you have little experience with machine vision and you need information about how to solve common inspection tasks with NI Vision Builder for Automated Inspecti
28. detection algorithm that extracts the contours in gray level values Gradient filters include the Prewitt and Sobel filters The brightness of a pixel in an image Increases the brightness of pixels in an image that are surrounded by other pixels with a higher intensity Reduces the brightness of pixels in an image that are surrounded by other pixels with a lower intensity An image with monochrome information Functions that perform morphological operations on a gray level image Hour The inverse of lowpass attenuation Emphasizes the intensity variations in an image detects edges or object boundaries and enhances fine details in an image Removes or attenuates low frequencies present in the frequency domain of the image A highpass frequency filter suppresses information related to slow variations of light intensities in the spatial image The inverse of lowpass truncation Indicates the quantitative distribution of the pixels of an image per gray level value Transforms the gray level values of the pixels of an image to occupy the entire range of the histogram thus increasing the contrast of the image The histogram range in an 8 bit image is 0 to 255 ni com histogram inversion histograph hit miss function HSI HSL HSV hue VO image image border Image Browser image buffer image definition National Instruments Corporation G 7 Glossary Finds the photometric negative of an ima
29. e Does not require shape information for the region Complete the following general steps to find features in an image using color location 1 Define a reference pattern in the form of a template image 2 Use the reference pattern to train the color location algorithm with IMAQ Learn Color Pattern 3 Define an image or an area of an image as the search area A small search area can reduce the time to find the features We 4 Set the Feature Mode control of IMAQ Setup Learn Color Pattern to Bu Color 5 Set the tolerances and parameters to specify how the algorithm operates at run time using IMAQ Setup Match Color Pattern 6 Test the color location algorithm on test images using IMAQ Match Bu Color Pattern 7 Verify the results using a ranking method You can save the template image using the IMAQ Write Image and Vision Info VI Machine Vision Searching and Matching Convert Pixel Coordinates to Real World Coordinates The measurement points you located with edge detection and pattern matching are in pixel coordinates If you need to make measurements using ow real world units use the IMAQ Convert Pixel to Real World VI Vision o Utilities Calibration to convert the pixel coordinates into real world units National Instruments Corporation 5 25 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks Make Measurements You can make different types of measurements either directly from th
30. grid use the Reference Points control of IMAQ Learn Calibration Template to specify the pixel to real world mapping National Instruments Corporation 6 5 IMAQ Vision for LabVIEW User Manual Chapter 6 Calibrating Images Specifying Scaling Factors Scaling factors are the real world distances between the dots in the calibration grid in the x and y directions and the units in which the distances are measured Use the X Step and Y Step elements of the Grid Descriptor control to specify the scaling factors Choosing a Region of Interest Define a learning ROI during the learning process to define a region of the calibration grid you want to learn The software ignores dot centers outside this region when it estimates the transformation Depending on the calibration options selected this is an effective way to increase correction speeds Set the learning ROI using the Calibration Learn Setup control of IMAQ Learn Calibration Template Ky Note The user defined learning ROI represents the area in which you are interested Do not confuse the learning ROI with the calibration ROI generated by the calibration algorithm Refer to Figure 6 6 for an illustration of calibration ROIs Choosing a Learning Algorithm Select a method in which to learn the calibration information perspective projection or nonlinear Figure 6 5 illustrates the types of errors your image can exhibit Figure 6 5a shows an image of a calibration grid with no errors Fig
31. not parallel to the main axis in the same search area The object contains a second distinct edge not parallel to the main axis ina separate search area Build a coordinate transformation based on edge detection using a single search area Object positioning accuracy better than 5 degrees Build a coordinate transformation based on edge detection using two distinct search areas Build a coordinate Build a coordinate transformation based on transformation based on pattern matching pattern matching shift invariant strategy rotation invariant strategy Figure 5 4 Building a Coordinate Transformation National Instruments Corporation 5 7 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks Set Search Areas Select ROIs in your images to limit the areas in which you perform your processing and inspection You can define ROIs interactively or programmatically Defining Regions Interactively Use the techniques described in Chapter 4 Performing Particle Analysis to select an ROI The following table shows which ROI to use with a given measurement VI Rotated rectangle IMAQ Find Pattern Machine Vision Find Patterns IMAQ Clamp Horizontal Max Machine Vision Measure Distances IMAQ Clamp Horizontal Min Machine Vision Measure Distances IMAQ Clamp Vertical Max Machine Vision Measure Distances IMAQ Clamp Vertical Min Machine Vision Measure Distances IMAQ Find Horizo
32. of particles in an image and an array of reports containing 11 of the most commonly used measurements including the particle area bounding rectangle and center of mass e IMAQ Particle Analysis Image Processing Analysis This VI returns an array containing your choice of up to 80 particle measurements Refer to Chapter 10 Particle Measurements of the IMAQ Vision Concepts Manual for a list of all the measurements that IMAQ Particle Analysis can return IMAQ Vision for LabVIEW User Manual 4 4 ni com Performing Machine Vision Tasks This chapter describes how to perform many common machine vision inspection tasks The most common inspection tasks are detecting the presence or absence of parts in an image and measuring the dimensions of parts to determine if they meet specifications Measurements are based on characteristic features of the object represented in the image Image processing algorithms traditionally classify the type of information contained in an image as edges surfaces and textures or patterns Different types of machine vision algorithms leverage and extract one or more types of information Edge detectors and derivative techniques such as rakes concentric rakes and spokes use edges represented in the image They locate with high accuracy the position of the edge of an object You can use edge detection to make such measurements as the width of the part which is a technique called clamping You al
33. points between a set of search lines within the search region and the edge of an object Specify the separation between the lines that the VIs use to detect edges The VIs determine the intersection points based on their contrast width and steepness The software calculates a best fit line with outliers rejected or a best fit circle through the points it found The VIs return the coordinates of the edges found Finding Edge Points Along One Search Contour iat Use the IMAQ Simple Edge VI Machine Vision Caliper and the IMAQ Edge Tool VI Machine Vision Caliper to find edge points along a contour You can find the first edge last edge or all edges along the contour Use IMAQ Simple Edge when your image contains little noise and the object and background are clearly differentiated Otherwise use IMAQ Edge Tool PhS alll m IMAQ Simple Edge and IMAQ Edge Tool require you to input the coordinates of the points along the search contour Use the IMAQ ROIProfile VI Image Processing Analysis to obtain the coordinates from the ROI descriptor of the contour If you have a straight line use the IMAQ GetPointsOnLine VI Machine Vision Analytic National Instruments Corporation 5 11 IMAQ Vision for LabVIEW User Manual Chapter 5 i ir Performing Machine Vision Tasks gr mi Geometry to obtain the points along the line instead of using an ROI descriptor IMAQ ROIProfile and IMAQ GetPointsOnLine determine the edge po
34. search area around the fiducial If you know before the matching process begins that the PCB can shift or rotate in the image within a fixed range as shown in Figure 5 1 1c and Figure 5 11d respectively you can limit the search for the fiducial to a small region of the image Figure 5 11 Selecting a Search Area for Grayscale Pattern Matching IMAQ Vision for LabVIEW User Manual 5 16 ni com Chapter 5 Performing Machine Vision Tasks Setting Matching Parameters and Tolerances Every pattern matching algorithm makes assumptions about the images and pattern matching parameters used in machine vision applications These assumptions work for a high percentage of the applications However there may be applications in which the assumptions used in the algorithm are not optimal Knowing your particular application and the images you want to process is useful in selecting the pattern matching HP parameters Use the IMAQ Setup Match Pattern 2 VI Machine Vision Searching and Matching to set the following parameters that influence the IMAQ Vision pattern matching algorithm match mode minimum contrast and rotation angle ranges Match Mode Set the match mode to control how the pattern matching algorithm treats the template at different orientations If you expect the orientation of valid matches to vary less than 5 from the template set the Match Mode control to Shift Invariant Otherwise set Match Mode to Rotation Invariant Sh
35. the IMAQ Overlay VIs Vision Utilities Overlays such as IMAQ Overlay Rectangle and IMAQ Overlay Text You also can use IMAQ Merge Overlay to merge your overlay data into your image Refer to the IMAQ Vision for LabVIEW Help for information about merging overlays How can I make my Vision for LabVIEW application work on my RT system if the application contains IMAQ Browser VIs If your application uses any of the IMAQ Browser VIs use IMAQ ImageToImage Vision Utilities Image Management to embed multiple images within a single image Why do I geta File Not Found error from my LabVIEW VI when I run it on LabVIEW RT When you run your LabVIEW RT application your VI is downloaded to your RT target but your support files such as images and templates are not The File I O routines in LabVIEW RT and IMAQ Vision always refer to files on the target machine which is the remote RT target in this case Use FTP to move your image files to the RT target Refer to your LabVIEW RT documentation for more information about transferring files to your RT target using FTP If you created a VI in the NI Vision Assistant selecting Image File for your Image Source setting causes your VI to return an error in the LabVIEW RT This is because the File Dialog function is not supported in the LabVIEW RT To avoid this error select Image Control or Image Acquisition Board as the Image Source IMAQ Vision for LabVIEW User Manual A 12 ni com Appendix
36. to improve the sharpness of transitions in the image or increase the overall signal to noise ratio of the image You can choose either a lowpass or highpass filter depending on your needs IMAQ Vision for LabVIEW User Manual 2 14 ni com Chapter 2 Getting Measurement Ready Images Lowpass filters remove insignificant details by smoothing the image removing sharp details and smoothing the edges between the objects and the background You can use the IMAQ LowPass VI Image F Processing Filters or define your own lowpass filter with the a IMAQ Convolute VI or IMAQ NthOrder VI Highpass filters emphasize details such as edges object boundaries or cracks These details represent sharp transitions in intensity value You can define your own highpass filter with IMAQ Convolute or IMAQ NthOrder PO or use the IMAQ EdgeDetection VI or IMAQ CannyEdgeDetection VI a Image Processing Filters IMAQ EdgeDetection allows you to find edges in an image using predefined edge detection kernels such as the Sobel Prewitt and Roberts kernels Convolution Filter IMAQ Convolute Image Processing Filters allows you to use a predefined set of lowpass and highpass filters Each filter is defined by a kernel of coefficients Use the IMAQ GetKernel VI Image Processing Filters to retrieve predefined kernels If the predefined kernels do not meet your needs define your own custom filter using a LabVIEW 2D array of floating point numbers Nth Order Fi
37. with an object surface creates the observed color of that object The color of a surface depends on the directions of illumination and the direction from which the surface is observed Two identical objects may have different appearances because of a difference in positioning or a change in the lighting conditions Figure 3 9 shows how light reflects differently off of the 3D surfaces of the fuses resulting in slightly different colors for identical fuses Compare the 3 amp fuse in the upper row with the 3 amp fuse in the lower row The difference in light reflection results in different color spectrums for identical fuses If you learn the color spectrum by drawing a region of interest inside the 3 amp fuse in the upper row and then do a color matching for the 3 amp fuse in the upper row you get a very high match score close to 1000 However the match score for the 3 amp fuse in the lower row is quite low at around 500 This problem could cause a mismatch for the color matching in a fuse box inspection process The color learning algorithm of IMAQ Vision uses a clustering process to find the representative colors from the color information specified by one or multiple regions in the image To create a representative color spectrum for all 3 amp fuses in the learning phase draw an ROI around the three amp fuse in the upper row hold down the lt Ctrl gt key and draw another ROI around the 3 amp fuse in the lower row The new color spectrum
38. with lookup tables filters grayscale morphology and Fast Fourier transforms Apply lookup table LUT transformations to highlight image details in areas containing significant information at the expense of other areas A LUT transformation converts input grayscale values in the source image into other grayscale values in the transformed image IMAQ Vision provides four VIs that directly or indirectly apply lookup tables to images e IMAQ MathLookup Image Processing Processing Converts the pixel values of an image by replacing them with values from a predefined lookup table IMAQ Vision has seven predefined lookup tables based on mathematical transformations Refer to Chapter 5 Image Processing of the IMAQ Vision Concepts Manual for more information about these lookup tables e IMAQ UserLookup Image Processing Processing Converts the pixel values of an image by replacing them with values from a user defined lookup table e IMAQ Equalize Image Processing Processing Distributes the grayscale values evenly within a given grayscale range Use IMAQ Equalize to increase the contrast in images containing few grayscale values e IMAQ Inverse Image Processing Processing Inverts the pixel intensities of an image to compute the negative of the image For example use IMAQ Inverse before applying an automatic threshold to your image if the background pixels are brighter than the object pixels Filter your image when you need
39. 3 6 Defining Regions Programmatically ccccccccccccssecessssessessseeeseeesseeeseeeseeeees 3 7 Defining Regions with MASK Sacre iiclenacaca ewes ieucile utscaondmiiasssteusbatueaeueaetecgiad 3 9 Measure Gray SCale Stalls MCS oorsee e ea r ke iibenebensemiakesentiesaes 3 9 Measure Color Statisties ecrire i I man veenseiae a tumeraua se 3 10 C OMIDAEIN OC OLOES seoska seia O 3 12 Learning Color TnitormatiOn ssid cisecssswueuteet nde veussiwuidduairiamtlavsnnddeianeess 3 12 Specifying the Color Information to Learn 0 0 0 cccccccccceeeeeeeeeees 3 13 Choosing a Color Representation Sensitivity ccccccccccseeeeeseeees 3 15 Fonorins Learned Colors sercuedncasdcddasenncacadsaseaensedcanaoaprargnteqovedemanases 3 16 Chapter 4 Performing Particle Analysis Creata Binan Matese aa a a a aae 4 1 Improve the Binary IMa Creina a N Na 4 2 Removing Unwanted Particles eeeeeeeeeeeeeseesseeeseessssessssesnsssssssssssssssssssssseese 4 3 Separating TOUCHING Particle S sic icivcasiuinochsabeermnas E aeaea Eare E 4 4 lhnprovin amp Particle Shapes isicis deisacvettininateddetacescdleuteealeddentuiadfausnuveliauaNencts 4 4 Make Panicle Moasu urcmie Me zsiros nare E A 4 4 IMAQ Vision for LabVIEW User Manual vi ni com Contents Chapter 5 Performing Machine Vision Tasks Locate Objects to INS pect sisca tae beans calae scarier a sits 5 2 Using Edge Detection to Build a Coordinate Transformation 00 5 3 Using Pat
40. A Vision for LabVIEW Real Time RT Video Out Errors Why do I have an invalid Video Out Mode To use the RT Video Out functionality in Vision for LabVIEW RT you must have a PXI controller featuring the 1815 graphics chipset such as the National Instruments PXI 8175 6 Series controllers If you are using a controller that does not support RT Video Out consider using Remote Display to display your images Why can t I see my images when I use RT Video Out LARI Use the IMAQ Video Out Display Mode VI to configure your video mode before you attempt to display your images This VI allows you to set your refresh frequency screen area and color depth ny Note If you are using a monitor that does not support high refresh frequencies your images cannot display correctly Refer to your monitor documentation for information about supported refresh frequencies National Instruments Corporation A 13 IMAQ Vision for LabVIEW User Manual Technical Support and Professional Services Visit the following sections of the National Instruments Web site at ni com for technical support and professional services Support Online technical support resources at ni com support include the following Self Help Resources For answers and solutions visit the award winning National Instruments Web site for software drivers and updates a searchable KnowledgeBase product manuals step by step troubleshooting wizards thousands of example progra
41. AND NAND OR NOR XOR XNOR and make pixel comparisons between an image and other images or a constant In addition one VI in this 1 4 ni com Machine Vision Chapter 1 Introduction to IMAQ Vision subpalette allows you to select regions in an image to process using a masking operation Frequency Domain A group of VIs that analyze and process images in the frequency domain Use these VIs to convert an image from the spatial domain to the frequency domain using a two dimensional Fast Fourier Transform FFT and convert from the frequency domain to the spatial domain using the inverse FFT These VIs also extract the magnitude phase real and imaginary planes of the complex image In addition these VIs allow you to convert complex images into complex 2D arrays and back Also in this subpalette are VIs that perform basic arithmetic operations such as addition subtraction multiplication and diviston between a complex image and other images or a constant Lastly some of these VIs allow you to filter images in the frequency domain Pa The IMAQ Machine Vision VIs are high level VIs that simplify common b machine vision tasks e Yo ae oa T T e e National Instruments Corporation Select Region of Interest A group of VIs that allow you to select a ROI tool draw specific ROIs in the image window and return information about ROIs with very little programming Coordinate System A group of VIs that fi
42. D or LED Identify Parts Under Inspection Classifying Samples Blea zap Eh KE aF th E IMAQ Vision for LabVIEW User Manual In addition to making measurements after you set regions of inspection you also can identify parts using classification optical character recognition OCR and barcode reading Use classification to identify an unknown object by comparing a set of its significant features to a set of features that conceptually represent classes of known objects Typical applications involving classification include the following Sorting Sorts objects of varied shapes For example sorting different mechanical parts on a conveyor belt into different bins Inspection Inspects objects by assigning each object an identification score and then rejecting objects that do not closely match members of the training set Before you classify objects you must train the Classifier Session with samples of the objects using the NI Classification Training Interface Go to Start Programs National Instruments Vision Classification Training to launch the NI Classification Training Interface After you have trained samples of the objects you want to classify use the following VIs to classify the objects 1 2 3 In the initialization part the of code use IMAQ Read Classifier File Machine Vision Classification to read in a Classifier that you created using the NI Classification Training Interface Use I
43. I 5 3 5 4 5 33 IMAQ Find CoordSys Pattern 2 VI 5 6 IMAQ Find CoordSys Pattern VI 5 6 5 33 IMAQ Find CoordSys Rect VI 5 3 5 33 IMAQ Find Horizontal Edge VI 5 9 5 32 IMAQ Find Pattern VI 5 33 IMAQ Find Vertical Edge VI 5 9 5 32 IMAQ Fit Circle 2 VI 5 27 IMAQ Fit Ellipse 2 VI 5 27 IMAQ Fit Line VI 5 27 IMAQ Get LCD ROI VI 5 28 IMAQ Get Meter 2 VI 5 27 IMAQ Get Meter VI 5 27 IMAQ GetFileInfo VI 2 8 IMAQ GetPalette VI 2 9 IMAQ GetPointsOnLine VI 5 12 IMAQ Grab Acquire VI 2 7 IMAQ Grab Setup VI 2 7 IMAQ GrayMorphology VI 2 16 IMAQ Histogram VI 2 13 IMAQ Histograph VI 2 13 IMAQ Image control 1 1 IMAQ Image Display control 1 1 IMAQ Image To Image VI A 12 IMAQ ImageToArray VI 2 8 IMAQ ImageToComplexPlane VI 2 18 IMAQ Initialize Timed Execution VI A 6 IMAQ IntegerToColorValue VI 3 12 IMAQ Inverse VI 2 14 IMAQ Label VI 3 9 ni com IMAQ Learn Color Pattern VI 5 20 IMAQ Learn Pattern 2 VI 5 15 IMAQ Light Meter Line VI 3 6 3 9 IMAQ Light Meter Point VI 3 6 3 9 IMAQ Light Meter Rectangle VI 3 6 3 9 IMAQ LineProfile VI 2 13 IMAQ Lines Intersection VI 5 27 IMAQ LowPass VI 2 15 IMAQ MathLookup VI 2 14 IMAQ Merge Overlay VI A 12 IMAQ Mid Line VI 5 27 IMAQ Morphology VI 4 4 IMAQ MultiThreshold VI 4 2 IMAQ OCR Dispose Session VI 5 29 IMAQ OCR Read Character Set File VI 5 29 IMAQ OCR Read Text VI 5 29 IMAQ Overlay Arc VI 5 32 IMAQ Ove
44. IMAQ IMAQ Vision for LabVIEW User Manual Ww NATIONAL August 2004 Edition gt INSTRUMENTS Part Number 371007A 01 Worldwide Technical Support and Product Information ni com National Instruments Corporate Headquarters 11500 North Mopac Expressway Austin Texas 78759 3504 USA Tel 512 683 0100 Worldwide Offices Australia 1800 300 800 Austria 43 0 662 45 79 90 0 Belgium 32 0 2 757 00 20 Brazil 55 11 3262 3599 Canada Calgary 403 274 9391 Canada Ottawa 613 233 5949 Canada Qu bec 450 510 3055 Canada Toronto 905 785 0085 Canada Vancouver 604 685 7530 China 86 21 6555 7838 Czech Republic 420 224 235 774 Denmark 45 45 76 26 00 Finland 385 0 9 725 725 11 France 33 0 1 48 14 24 24 Germany 49 0 89 741 31 30 India 91 80 51190000 Israel 972 0 3 6393737 Italy 39 02 413091 Japan 81 3 5472 2970 Korea 82 02 3451 3400 Malaysia 603 9131 0918 Mexico 01 800 010 0793 Netherlands 31 0 348 433 466 New Zealand 0800 553 322 Norway 47 0 66 90 76 60 Poland 48 22 3390150 Portugal 351 210 311 210 Russia 7 095 783 68 51 Singapore 65 6226 5886 Slovenia 386 3 425 4200 South Africa 27 0 11 805 8197 Spain 34 91 640 0085 Sweden 46 0 8 587 895 00 Switzerland 41 56 200 51 51 Taiwan 886 2 2528 7227 Thailand 662 992 7519 United Kingdom 44 0 1635 523545 For further support information refer to the Technical Support and Professional Services appendix To comment on National Instruments documentation refer to the National
45. Instruments Web site at ni com info and enter the info code feedback 2000 2004 National Instruments Corporation All rights reserved Important Information Warranty The media on which you receive National Instruments software are warranted not to fail to execute programming instructions due to defects in materials and workmanship for a period of 90 days from date of shipment as evidenced by receipts or other documentation National Instruments will at its option repair or replace software media that do not execute programming instructions if National Instruments receives notice of such defects during the warranty period National Instruments does not warrant that the operation of the software shall be uninterrupted or error free A Return Material Authorization RMA number must be obtained from the factory and clearly marked on the outside of the package before any equipment will be accepted for warranty work National Instruments will pay the shipping costs of returning to the owner parts which are covered by warranty National Instruments believes that the information in this document is accurate The document has been carefully reviewed for technical accuracy In the event that technical or typographical errors exist National Instruments reserves the right to make changes to subsequent editions of this document without prior notice to holders of this edition The reader should consult National Instruments if errors are suspected
46. Logical Operations eeeeeesseessssessssessssssssssssssssssss 2 6 ACUN OF WCAG aN MINAG ie tava detans anole ananeesalen tone coudenesgatbasek Docsite 2 6 Disphiy aN na Gey es aanateaa santos sce E canes Weeenas Sates eaeadeastouke 2 8 External Window Display oeisio aE 2 8 piace Display COMMO a mice sel an swritleisvte a a a A E E 2 9 Atache abran on M Onna Oesen N i Ne N tears 2 12 Analyze an Da ea a a EE E EE 2 12 National Instruments Corporation V IMAQ Vision for LabVIEW User Manual Contents TPO VS Ai Mat Cana ee cc Sanaa e TEN 2 14 Lookup PA DICS xp ccgcreeit ieuccacitesmincaielcpunisutanAiatedtaccntenndeimoutsNeanlnomedeucemanieates 2 14 PO ecto cea se tara aes Sai arse cea na EE eee dreamt 2 14 CONVO MITIOM UATE esns a E 2 15 NEO BU NeT 5525s E denereelontaesetetes 2 15 Grayscale Morpholo Vedios scscai Mimaseadsea tute didadsuidaiiastetitdaa tonne tr seuaelenabeiieles 2 15 PEL eea N 2 16 Advanced Opera ONS Sines nscnieninatiainotensielentetitnannmagsantietssnestts 2 18 Chapter 3 Making Grayscale and Color Measurements Detine Reeions Of liEIeS beaa alee ee eee 3 1 Defining Regions Interactivel yenen a E 3 3 Defining an ROI in the Image Display Control eee 3 3 Defining an ROI in an External Window cc ecccecceeeeeeeeeeeeeeees 3 4 Defining an ROI Using an ROI Constructor ccccccceeeeesseeeeeeees 3 4 Tools Palette Transformation ccceccceeeeeesseesnecceeeeeeeeeeeeeeeeeeees
47. MAQ Classify Machine Vision Classification to classify the object inside the ROI of the image under inspection into one of the classes you created using the NI Classification Training Interface Use IMAQ Dispose Classifier Machine Vision Classification to free the resources that the Classifier Session used 5 28 ni com Chapter 5 Performing Machine Vision Tasks Figure 5 13 shows LabVIEW pseudocode of a typical classification VI Read a Classifier File Dispose of the Classifier Session Acquire and Preprocess the Image Path to the Trained Classifier File Locate the Sample to Classify Class Classify the Sample Stop Figure 5 13 Sample Code of a Classification Application Reading Characters Use OCR to read text and or characters in an image Typical uses for OCR in an inspection application include identifying or classifying components Before you read text and or characters in an image you must train the OCR Session with samples of the characters using the NI OCR Training Interface Go to Start Programs National Instruments Vision OCR Training to launch the NI OCR Training Interface After you have trained samples of the characters you want to read use the following VIs to read the characters 1 In the initialization part the of code use IMAQ OCR Read Character Aize Set File Machine Vision OCR to read in a session that you created using the NI OCR Training Interface ao 2 Use IMAQ OCR Read Text Machine
48. OF THE SOFTWARE PRODUCTS CAN BE IMPAIRED BY ADVERSE FACTORS INCLUDING BUT NOT LIMITED TO FLUCTUATIONS IN ELECTRICAL POWER SUPPLY COMPUTER HARDWARE MALFUNCTIONS COMPUTER OPERATING SYSTEM SOFTWARE FITNESS FITNESS OF COMPILERS AND DEVELOPMENT SOFTWARE USED TO DEVELOP AN APPLICATION INSTALLATION ERRORS SOFTWARE AND HARDWARE COMPATIBILITY PROBLEMS MALFUNCTIONS OR FAILURES OF ELECTRONIC MONITORING OR CONTROL DEVICES TRANSIENT FAILURES OF ELECTRONIC SYSTEMS HARDWARE AND OR SOFTWARE UNANTICIPATED USES OR MISUSES OR ERRORS ON THE PART OF THE USER OR APPLICATIONS DESIGNER ADVERSE FACTORS SUCH AS THESE ARE HEREAFTER COLLECTIVELY TERMED SYSTEM FAILURES ANY APPLICATION WHERE A SYSTEM FAILURE WOULD CREATE A RISK OF HARM TO PROPERTY OR PERSONS INCLUDING THE RISK OF BODILY INJURY AND DEATH SHOULD NOT BE RELIANT SOLELY UPON ONE FORM OF ELECTRONIC SYSTEM DUE TO THE RISK OF SYSTEM FAILURE TO AVOID DAMAGE INJURY OR DEATH THE USER OR APPLICATION DESIGNER MUST TAKE REASONABLY PRUDENT STEPS TO PROTECT AGAINST SYSTEM FAILURES INCLUDING BUT NOT LIMITED TO BACK UP OR SHUT DOWN MECHANISMS BECAUSE EACH END USER SYSTEM IS CUSTOMIZED AND DIFFERS FROM NATIONAL INSTRUMENTS TESTING PLATFORMS AND BECAUSE A USER OR APPLICATION DESIGNER MAY USE NATIONAL INSTRUMENTS PRODUCTS IN COMBINATION WITH OTHER PRODUCTS IN A MANNER NOT EVALUATED OR CONTEMPLATED BY NATIONAL INSTRUMENTS THE USER OR APPLICATION DESIGNER IS ULTIMATELY RESPONSIBLE FOR VERIFYING AND VALIDATING THE S
49. UITABILITY OF NATIONAL INSTRUMENTS PRODUCTS WHENEVER NATIONAL INSTRUMENTS PRODUCTS ARE INCORPORATED IN A SYSTEM OR APPLICATION INCLUDING WITHOUT LIMITATION THE APPROPRIATE DESIGN PROCESS AND SAFETY LEVEL OF SUCH SYSTEM OR APPLICATION Contents About This Manual CONVENON oaoa a E sade sacs acndeumeeceasumetaredeucessesunsscubacseecemecss xi Related DOCUMeN All O Missi sseteve rises selects ierraeetenldvautanantwesiasencts E xii IMAO V ON E N xii NEVISIOrASS Staani an a O xii NI Vision Builder for Automated Inspection ccsseeeeseeeeseeeeseeeeeseeeeees xii Omer DocumentaviOn sassi A EA xili Chapter 1 Introduction to IMAQ Vision A Dot VEN COV S Oa aaa oe a a aaa 1 1 IMAO Mision Control dlette srei i TE a A 1 1 IMAO Virom PUNnCHON Palee S E E ANT 1 2 NISIOM WHITES cicca a E a 1 2 Image Processio monoa a E sd nde anne eenadcasec wos eeees 1 4 Machine VISO enan a a 1 5 How to Create IMAQ Vision Applications cccccceecessseeeeceseeeeeeeeeeeeeeeeeeeeeeeseeeeeeess 1 6 Chapter 2 Getting Measurement Ready Images Set Up Vout Imaging SV Stemi siselen cede ste rsacetsit danevac SE E vee EREEREER 2 1 Calibrate our Marmo Syste exisse e a a 2 2 Cree AM TMA Eege Ea a vag E a a 2 2 Input and Output Combinations cceccccceesceeseceesecsssessssssssssesseseseeseseeseeseees 2 4 MASE Analys iSe EE a Raa 2 4 BASS Mask Socorro N a a a a E 2 4 mace FINE zenna a a aaa 2 5 Fase Process IS e e a a i 2 5 Arithmetic and
50. User Manual l 2 determinism A 4 diagnostic tools NI resources B 1 displaying images 2 8 Remote Display A 3 results of inspection process 5 31 distance measurements 5 26 distortion correcting See calibration documentation conventions used in manual xi NI resources B 1 related documentation xii drivers NI resources B 1 NI IMAQ xiii 1 3 2 2 A 1 A 2 E edge detection building coordinate reference 5 3 finding measurement points along multiple search contours 5 12 along one search contour 5 11 lines or circles 5 9 error map for calibration 6 7 examples NI resources B 1 external window displaying images 2 8 F Fast Fourier Transform FFT 2 16 filters convolution 2 15 highpass 2 15 highpass frequency filters 2 17 improving images 2 14 lowpass 2 15 lowpass frequency filters 2 17 Nth order 2 15 finding measurement points See measurement points finding ni com frequency domain 2 17 function palettes Image Processing 1 4 Machine Vision 1 5 Vision Utilities 1 2 G geometrical measurements 5 27 grayscale and color measurements color statistics color comparison 3 12 learning color information 3 12 primary components of color images figures 3 11 defining regions of interest interactively 3 3 programmatically 3 7 using masks 3 9 grayscale statistics 3 9 area 3 9 energy center 3 10 light intensity 3 9 maximum intensity 3 9 mean intensity 3 9 minimum in
51. Vision OCR to read the Rize characters inside the ROI of the image under inspection ii 3 Use IMAQ OCR Dispose Session Machine Vision OCR to free the Alze resources that the OCR Session used National Instruments Corporation 5 29 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks Reading Barcodes Use barcode reading VIs to read values encoded into 1D barcodes Data Matrix barcodes and PDF417 barcodes Reading 1D Barcodes mr Use IMAQ Read Barcode Machine Vision Instrument Readers to read e values encoded in a 1D barcode Locate the barcode in the image using one of the techniques described in the Locate Objects to Inspect and Set Search Areas section of this chapter Then pass the ROI Descriptor of the location into IMAQ Read Barcode Specify the type of 1D barcode in the application using the Barcode Type control IMAQ Vision supports the following 1D barcode types Codabar Code 39 Code 93 Code 128 EAN 8 EAN 13 Interleaved 2 of 5 MSI and UPCA Reading Data Matrix Barcodes Use IMAQ Read Data Matrix Barcode Machine Vision Instrument Readers to read values encoded in a Data Matrix barcode The VI can automatically determine the location of the barcode and appropriate search options for your application However you can improve the performance of the application by specifying control values specific to your application IMAQ Read Data Matrix Barcode can locate automatically one or m
52. While your application is running on the RT target your user can use the ROI tools associated with the Image Display control to select their ROI on the host computer Use the ROI property node in your application to get the user selected ROI If you are using LabVIEW RT 7 1 or later you can use the Get Last Event invoke node in your application to determine when a user has drawn a new ROI and to get basic properties of the new ROI You can also use the Clear ROI invoke node to ensure the Image Display control is not displaying an IMAQ Vision for LabVIEW User Manual A 10 ni com Appendix A Vision for LabVIEW Real Time ROI when your application begins execution Refer to Extract Example vi located in examples vision 2 Functions Image Management to learn more about using these invoke nodes in an application ar For all versions of LabVIEW RT you can use the IMAQ Construct ROI VI S Vision Utilities External Display to allow the user to select an ROI LabVIEW displays the ROI selection window on the host computer and outputs the selected ROI to the VI running on the RT target Similarly you can use the IMAQ WindDraw VI Vision Utilities External Display to display the inspection image on the host computer You can then use the IMAQ WindToolsShow VI Vision Utilities External Display to display the tools dialog on the host computer Your user would then use the ROI tools to select their ROI in the image display window Use the IMAQ Wi
53. a chromaticity closing clustering CLUT color image color space complex image connectivity National Instruments Corporation G 3 Glossary A measurement function that finds edge pairs along a specified path in the image This function performs an edge extraction and then finds edge pairs based on specified criteria such as the distance between the leading and trailing edges edge contrasts and so forth Controller Area Network A serial bus finding increasing use as a device level network for industrial automation CAN was developed by Bosch to address the needs of in vehicle automotive communications The point on an object where all the mass of the object could be concentrated without changing the first moment of the object about any axis The color information in a video signal The combination of hue and saturation The relationship between chromaticity and brightness characterizes a color A dilation followed by an erosion A closing fills small holes in objects and smooths the boundaries of objects A technique where the image is sorted within a discrete number of classes corresponding to the number of phases perceived in an image The gray values and a barycenter are determined for each class This process is repeated until a value is obtained that represents the center of mass for each phase or class Color lookup table A table for converting the value of a pixel in an image into a red green and b
54. abVIEW User Manual Index for machine vision inspection 5 8 ROI constructor window 3 5 tools palette functions table 3 2 tools palette tools and information figure 3 7 programmatically for machine vision inspection 5 9 specifying ROI elements and parameters 3 7 using VIs 3 8 using masks 3 9 related documentation xii Remote Display A 3 resource management A 5 ROI See regions of interest defining RT Video Out A 2 A 4 A 13 S samples classifying 5 28 saving calibration information 6 10 scaling mode for calibration 6 8 search contour finding points along edge 5 11 software NI resources B 1 specifying information to learn using entire image 3 13 using multiple regions in image 3 14 using region in image 3 14 support technical B 1 IMAQ Vision for LabVIEW User Manual l 8 T technical support B 1 template for calibration defining 6 2 template images defining color pattern matching 5 19 pattern matching 5 13 learning color pattern matching 5 20 pattern matching 5 15 time bounded execution A 4 A 5 A 6 tools palette functions table 3 2 training and certification NI resources B 1 troubleshooting NI resources B 1 truncation highpass 2 17 lowpass 2 17 V validating calibration 6 9 verifying pattern matching 5 18 Vision Utilities function palettes 1 2 W Web resources B 1 ni com
55. al Index Numerics 16 bit color images 3 11 1D barcodes reading 5 30 8 bit color images 3 11 A acquiring measurement ready images See measurement ready images acquiring analytic geometry measurements 5 27 analyzing images 2 12 application development general steps figure 1 7 inspection steps figure 1 8 attaching calibration information to images 2 12 6 10 attenuation highpass 2 17 lowpass 2 17 AVI files 2 8 barcodes reading data matrix barcodes 5 30 reading PDF417 barcodes 5 31 binary images See particle analysis binary morphology 4 2 C calibration attaching calibration information to images 2 12 6 10 defining reference coordinate system 6 3 defining template 6 2 for perspective and nonlinear distortion 6 1 National Instruments Corporation learning calibration information choosing learning algorithm 6 6 choosing ROI 6 6 correction table 6 8 learning score and error map 6 7 scaling mode 6 8 voiding calibration 6 9 overview 2 2 saving calibration information 6 10 simple calibration 6 9 characters reading 5 29 circles finding points along edge 5 9 Classification Training Interface 5 28 classifying samples 5 28 color comparison 3 12 color information learning See learning color information color location algorithms for finding measurement points 5 25 color measurements See grayscale and color measurements color pattern matching See also pattern matching
56. alization Reduces the size of an object along its boundary and eliminates isolated points in the image Expand the high gray level information in an image while suppressing low gray level information Decreases brightness and increases contrast in bright regions of an image and decreases contrast in dark regions of an image Fast Fourier Transform A method used to compute the Fourier transform of an image A reference pattern on a part that helps a machine vision application find the part location and orientation in an image Transforms an image from the spatial domain to the frequency domain The counterparts of spatial filters in the frequency domain For images frequency information is in the form of spatial frequency Feet A set of software instructions executed by a single line of code that may have input and or output parameters and returns a value when executed IMAQ Vision for LabVIEW User Manual Glossary G gamma gradient convolution filter gradient filter gray level gray level dilation gray level erosion grayscale image grayscale morphology H h highpass attenuation highpass filter highpass frequency filter highpass truncation histogram histogram equalization IMAQ Vision for LabVIEW User Manual G 6 The nonlinear change in the difference between the video signal s brightness level and the voltage level needed to produce that brightness See gradient filter An edge
57. ansferring large images IMAQ Remote Compression allows you to specify compression settings for those images to reduce the network bandwidth used by the display process In addition compressing images may increase your display rates on slower networks e IMAQ Remote Compression uses two types of compression algorithms Use the lossy JPEG compression algorithm on grayscale and color images Use the lossless Packed Binary compression algorithm on binary images Refer to the IMAQ Vision for LabVIEW Help for more information about the IMAQ Remote Compression VI Kj Note JPEG Compression may result in data degradation of the displayed image There is no degradation of the image during processing Test various compression settings to find the right balance for your application e Using Remote Display can affect the timing performance of your IMAQ Vision VIs Do not use Remote Display if your program contains a time critical loop e Disconnecting your remote system from your host machine disables Remote Display Disabled Remote Display VIs do not affect the National Instruments Corporation A 3 IMAQ Vision for LabVIEW User Manual Appendix A Vision for LabVIEW Real Time performance of your application When you reconnect your remote system and host machine Remote Display is automatically re enabled e Use RT Video Out instead of Remote Display on deployed systems Remote Display requires a LabVIEW front panel and deployed systems do not ha
58. aring Resources Allocate any resource whose exact size you know before the time limit is started This encourages optimal use of the reserved resources and provides maximum flexibility System resources allocated before timed execution are available at anytime Reserved resources allocated inside the time bounded portion of your code are not guaranteed to be available outside the timed environment Therefore you should preallocate as much as possible before entering the time bounded portion of your code When time bounded execution begins changes to system resources by IMAQ Vision algorithms such as resizing an existing image generate an error Images can be created only in system resources In addition special image changes performed by learning a pattern calibrating an image or adding an overlay also require system resources This is primarily because they have to exist outside the timed environment These operations are prohibited during time bounded execution Performing Time Bounded Vision Operations To limit the execution time of a block of vision operations make the following modifications e Isolate the portion of code to time bound in an independent VI e Set the independent VI s execution priority to time critical so that lower priority processes do not interrupt the timed execution Refer to the LabVIEW Real Time Module User Manual for information about program architecture e Turn off automated error handling so th
59. art surfaces Analyzes groups of pixels within an image and returns information about the size shape position and pixel connectivity Typical applications include testing the quality of parts analyzing defects locating objects and sorting objects A set of high level software functions such as NI IMAQ that control specific plug in computer boards Instrument drivers are available in several forms ranging from a function callable in a programming language to a VI in LabVIEW IMAQ Vision for LabVIEW User Manual G 8 ni com intensity intensity calibration intensity profile intensity range intensity threshold jitter JPEG K kernel L labeling LabVIEW National Instruments Corporation G 9 Glossary The sum of the red green and blue primary colors divided by three Red Green Blue 3 Assigns user defined quantities such as optical densities or concentrations to the gray level values in an image The gray level distribution of the pixels along an ROI in an image Defines the range of gray level values in an object of an image Characterizes an object based on the range of gray level values in the object If the intensity range of the object falls within the user specified range it is considered an object Otherwise it is considered part of the background The maximum amount of time that the execution of an algorithm varies from one execution to the next Joint Photographic Experts Group
60. at dialog boxes are not generated when an error occurs National Instruments Corporation A 7 IMAQ Vision for LabVIEW User Manual Appendix A Vision for LabVIEW Real Time a e Replace all Vision VIs in the time bounded operation with their time bounded counterparts located in Preallocated 11b Using a Vision VI that is not time bounded generates a run time error if the time limit is set Replacing the VIs ensures that Vision algorithms do not request resources from the system while running e Call IMAQ Start Timed Execution Vision Utilities IMAQ RT at the beginning of the vision block to initiate the time limit Use IMAQ Stop Timed Execution Vision Utilities IMAQ RT to turn off the time limit at the end of the Vision block Connect the error output from IMAQ Start Timed Execution to the Vision VIs in sequential order ending with IMAQ Stop Timed Execution When time expires and the processing is not complete the Vision VI executing at that moment generates a special timeout error The error cluster propagates the timeout condition reducing overall execution jitter Attempting to start an additional time limit results in an error For vision algorithms working with images serialized processing is crucial because an image may be shared among multiple vision routines running in parallel When changes to the image are required the image is blocked from access until the updates are completed This is another form of resource contentio
61. bVIEW User Manual G 10 ni com luminance LUT machine vision mask FFT filter match score MB median filter memory buffer MMX morphological transformations M skeleton function National Instruments Corporation G 11 Glossary See luma Lookup table A table containing values used to transform the gray level values of an image For each gray level value in the image the corresponding new value is obtained from the lookup table 1 Mega the standard metric prefix for 1 million or 10 when used with units of measure such as volts and hertz 2 Mega the prefix for 1 048 576 or 220 when used with B to quantify data or computer memory An automated application that performs a set of visual inspection tasks Removes frequencies contained in a mask range specified by the user A number ranging from 0 to 1000 that indicates how closely an acquired image matches the template image A match score of 1000 indicates a perfect match A match score of 0 indicates no match Megabyte of memory A lowpass filter that assigns to each pixel the median value of its neighbors This filter effectively removes isolated pixels without blurring the contours of objects See buffer Multimedia Extensions An Intel chip based technology that allows parallel operations on integers which results in accelerated processing of 8 bit images Extract and alter the structure of objects in an image You can use these transfo
62. calibration procedure automatically determines the direction of the horizontal axis in the real world The vertical axis direction can either be indirect as shown in Figure 6 2a or direct as shown in Figure 6 2b Figure 6 2 Axis Direction in the Image Plane If you do not specify a coordinate system the calibration process defines a default coordinate system If you specify a grid for the calibration process the software defines the following default coordinate system as shown in Figure 6 3 e The origin is placed at the center of the leftmost topmost dot in the calibration grid e The angle is set to 0 This aligns the x axis with the first row of dots in the grid as shown in Figure 6 3b e The axis direction is set to Indirect This aligns the y axis to the first column of the dots in the grid as shown in Figure 6 3b National Instruments Corporation 6 3 IMAQ Vision for LabVIEW User Manual Chapter 6 Calibrating Images c i t y 1 Origin of a Calibration Grid in the Real World 2 Origin of the Same Calibration Grid in an Image Figure 6 3 A Calibration Grid and an Image of the Grid If you specify a list of points instead of a grid for the calibration process the software defines a default coordinate system as follows 1 The origin is placed at the point in the list with the lowest x coordinate value and then the lowest y coordinate value 2 The angle is set to 0 The axis direction is s
63. ccceceeeeeeeeeeeeeeeeeees A 2 Remote Display fecaria tates iadenatescesatnattesenssna a G A 3 RTF Vdo Ouh eeeera anion gett aan laa nelemcusoahtseeca A 4 Determinism in Vision for LabVIEW Real Time ccccccceccsssssseeeseeeeeeeeeeeeeeeeeeeees A 4 Determinism versus Time Bounded Execution ccccccccccceccceeeeeeeeeeeeeeeees A 5 Hmo Bounded EXcCuUNO iiaee o a A 6 Initializing the Timed Environment c sssseeeccecceeeeceeeeeeeeeees A 6 Prepar ne RESOUICES sasrsoraaronimoianorn ana a a ican ubastanabe A 7 Performing Time Bounded Vision Operations ccccccccccceeeeeeeees A 7 Closing the Timed Environment sraao A 9 mage FeS peewee yee eee teres Tat E A iene fe rity a7 Terese renee Year Ore ENTE e rT T Te A 9 BEDO I 4 aan acasnacden nance taccasenbsoocnne E O a O A 9 PTOWDICSHOOU I E eraen a a a aa a a Ra a A 10 Remot Dip hy ENO E aie a e a NNG A 10 Programima ENO c E R A 11 RT Wie G8 OU ENOS aens Gates tats teccutoncstanensodee hen gnencssendedoosessesasoecguotmbeaseteses A 13 IMAQ Vision for LabVIEW User Manual viii ni com Contents Appendix B Technical Support and Professional Services Glossary Index National Instruments Corporation Ix IMAQ Vision for LabVIEW User Manual About This Manual Conventions Y ig bold italic monospace monospace bold The IMAQ Vision for LabVIEW User Manual is intended for engineers and scientists who have knowledge of the LabVIEW programm
64. cessed is set to the Nth pixel value where N is the order of the filter The number of arrays of pixels that compose the image A gray level or pseudo color image is composed of one plane An RGB image is composed of three planes one for the red component one for the blue component and one for the green component Optical Character Recognition The ability of a machine to read human readable text Optical Character Verification A machine vision application that inspects the quality of printed characters G 12 ni com offset opening operators optical representation outer gradient P palette particle particle analysis pattern matching picture element pixel pixel aspect ratio pixel calibration pixel depth National Instruments Corporation G 13 Glossary The coordinate position in an image where you want to place the origin of another image Setting an offset is useful when performing mask operations An erosion followed by a dilation An opening removes small objects and smooths boundaries of objects in the image Allow masking combination and comparison of images You can use arithmetic and logic operators in IMAQ Vision Contains the low frequency information at the center and the high frequency information at the corners of an FFT transformed image Finds the outer boundary of objects The gradation of colors used to display an image on screen usually defined by a CLUT A co
65. color planes from an image replace the planes of a color image with new data convert a color image to and from a 2D array read and set pixel values in a color image and convert pixel values from one color space to another IMAQ RT A group of VIs that provide functionality for using NI IMAQ and IMAQ Vision with LabVIEW RT Use these VIs to display images to Video Out on your RT system to control the compression setting for sending images over the network and to time bound your processing VIs on a LabVIEW RT system 1 3 IMAQ Vision for LabVIEW User Manual Chapter 1 Introduction to IMAQ Vision Image Processing e IMAQ Vision for LabVIEW User Manual Use the Image Processing functions to analyze filter and process images in IMAQ Vision Processing A group of VIs that process grayscale and binary images Use these VIs to convert a grayscale image into a binary image using different thresholding techniques You also can use these VIs to transform images using predefined or custom lookup tables change the contrast information in the image and invert the values in an image Filters A group of VIs that filter an image to enhance the information in the image Use these VIs to smooth an image remove noise and highlight or enhance edges in the image You can use a predefined convolution kernel or create custom convolution kernels Morphology A group of VIs that perform morphological operations on an image Some of these VI
66. connection between your host machine and RT target during development to configure the RT target and to download software and code from your host machine onto the RT target This network connection is optional at runtime Deployed System When you have configured your host development system you can set up and configure additional LabVIEW RT targets for deployment These deployed systems use the same hardware and software as your development LabVIEW RT target but they do not require Windows for configuration Instead of using Windows for configuration copy your configuration information from your development RT target to the deployment system NI IMAQ and Vision for LabVIEW Real Time Installation Set up your RT target by installing the LabVIEW Real Time Module and NI IMAQ Refer to Chapter 6 NJ IMAQ for LabVIEW Real Time of the NI IMAQ User Manual for detailed instructions Use MAX to install IMAQ Vision for LabVIEW and any other necessary LabVIEW RT components from your host machine onto your RT target system Refer to the Measurement amp Automation Explorer Remote Systems Help for specific information within MAX go to Help Help Topics Remote Systems When your RT target is set up you can write and execute IMAQ Vision code just as you would on a Windows based system Image Display in Vision for LabVIEW Real Time Vision for LabVIEW RT gives you two options for displaying images Remote Display and RT Video Out Use Remote Di
67. ded execution is no longer needed call IMAQ Uninitialize Timed Execution Vision Utilities IM AQ RT to release the resources reserved at initialization When the environment is uninitialized calls to Dam IMAQ Start Timed Execution produce an error Image Files Many applications require you to use external files such as the template files used by pattern matching and spatial calibration functions Before running your application on an RT target you must use FTP to transfer any external image files from your host machine to your remote target You can use MAX 3 0 and later to FTP images to your RT target Refer to the LabVIEW Real Time Module User Manual for more information about using FTP Deployment When you have finished developing your Vision for LabVIEW RT application you may want to deploy that application to a number of remote systems To achieve consistent results from your Vision for LabVIEW RT application you must configure these deployed systems with the same settings you used for your development system ai Note Each deployed system must have its own embedded real time controller and software Visit ni com for ordering information Note You must purchase a Vision for LabVIEW RT run time license and a LabVIEW Real Time Module run time license for each deployed Vision for LabVIEW RT system Visit ni com for more information about purchasing run time licenses Nai National Instruments Corporation A 9 IMAQ
68. defining search area 5 21 defining template images 5 19 setting matching parameters and tolerances color score weight 5 24 color sensitivity 5 23 minimum contrast 5 24 rotation angle ranges 5 24 search strategy 5 23 testing search tool on test images 5 24 training pattern matching tool using reference pattern 5 20 IMAQ Vision for LabVIEW User Manual Index color statistics color comparison 3 12 learning color information 3 13 3 14 choosing color representation sensitivity 3 15 ignoring learned colors 3 16 specifying information to learn 3 13 primary components of color images figures 3 11 connectivity 4 3 connector pane examples image analysis 2 4 image mask 2 4 contour finding points along edge 5 11 control palette Image Display control 2 9 IMAQ Image control 1 1 IMAQ Image Display control 1 1 IMAQ Vision controls 1 1 Machine Vision controls 1 2 conventions used in the manual xi converting pixel coordinates to real world coordinates 5 25 convolution filters 2 15 coordinate reference building for machine vision choosing method figure 5 7 edge detection 5 3 pattern matching 5 6 defining for calibration 6 3 coordinates converting pixel to real world coordinates 5 25 correction table for calibration 6 8 creating applications See application development creating images See images D data matrix barcodes reading 5 30 deployment application xiii A 9 IMAQ Vision for LabVIEW
69. e image or from points that you detect in the image Making Distance Measurements Use clamp VIs Machine Vision Measure Distances to measure the separation between two edges in a rectangular search region Specify the parameters for edge detection and the separation between the search lines that you want to use within the search region to find the edges Lb Kp Note Use the IMAQ Select Rectangle VI Machine Vision Select Region of Interest to generate a valid input search region for the clamp VIs First the VIs use the rake function to detect points along two edges of the object under inspection Then the VIs compute the distance between the points detected on the edges along each search line of the rake The VIs return the largest or smallest distance in either the horizontal or vertical direction and they output the coordinates of all the edge points that they find The following list describes the available clamp VIs e IMAQ Clamp Horizontal Max Measures the largest horizontal separation between two edges in a rectangular search region e IMAQ Clamp Horizontal Min Finds the smallest horizontal separation between two vertically oriented edges IMAQ Clamp Vertical Max Finds the largest vertical separation between two horizontally oriented edges e IMAQ Clamp Vertical Min Finds the smallest vertical separation between two horizontally oriented edges Use the IMAQ Point Distances VI Machine Vision Analytic Geometry t
70. e Attach Calibration Information section of this chapter for more information Then depending on your needs you can perform one of the following steps e Use the real world measurements options on the Particle Analysis and Particle Analysis Reports VIs to get real world particle shape parameters without correcting the image National Instruments Corporation 6 1 IMAQ Vision for LabVIEW User Manual Chapter 6 Calibrating Images e Use the calibration information to convert pixel coordinates to real world coordinates without correcting the image e Create a distortion free image by correcting the image for perspective errors and lens aberrations Refer to Chapter 6 Calibrating Images for more information about applying calibration information before making measurements Defining a Calibration Template You can define a calibration template by supplying an image of a grid or providing a list of pixel coordinates and their corresponding real world coordinates This section discusses in detail the grid method of defining a calibration template in detail A calibration template is a user defined grid of circular dots As shown in Figure 6 1 the grid has constant spacings in the x and y directions You can use any grid but follow these guidelines for best results e The displacement in the x and y directions should be equal dx dy e The dots should cover the entire required working area e The radius of the dots in the acquired
71. e containing the calibration information and a destination image that you want to calibrate The output image is your inspection image with the calibration information attached to it Refer to Chapter 6 Calibrating Images for detailed information about calibration Kp Note Because calibration information is part of the image it is propagated throughout the processing and analysis of the image Functions that modify the image size such as geometrical transforms void the calibration information Use IMAQ Write Image and Bye Vision Info Vision Utilities Calibration to save the image and all of the attached calibration information to a file Analyze an Image When you acquire and display an image you may want to analyze the contents of the image for the following reasons e To determine if the image quality is sufficient for your inspection task e To obtain the values of parameters that you want to use in processing functions during the inspection process The histogram and line profile tools can help you analyze the quality of your images IMAQ Vision for LabVIEW User Manual 2 12 ni com Chapter 2 Getting Measurement Ready Images Use the IMAQ Histograph and IMAQ Histogram VIs Image Processing Analysis to analyze the overall grayscale distribution in the image Use the histogram of the image to analyze two important criteria that define the quality of an image saturation and contrast If your image is underexposed becau
72. e eesmise a AE 6 2 Defining a Reference Coordinate System cccccccsscssssssssssssssesseeesseeeeseeees 6 3 Learning Calibration Information seeeeeessseesesesesssssssssessssssssssssssssssssssssesese 6 5 Specifying Scaling Factors eseeesseensseessssssssssssssssssssssssnsssnnsssssssss 6 6 Choosing a Region of Interest a Acicscainiceaitetaviceaiianesteadidwoisutecsenseacedas 6 6 Choosing a Learning Algorithm cccccccccsecsssecceeeeeeeeeeeeeeeaeenaaes 6 6 Usmo the Learin SCOLE J ierednsivisadareonesennsednacusadsscananenrendancbObersacestes 6 7 Learning the Eror Mapian A a 6 8 Leaming the Correction Tabie sorcier Ne EN E 6 8 Setting the Scaling Method seseeeseeeseeessnessssssssssssssssssssssssssssssssssss 6 8 Cali bration Inv alt atl ON sieurs ene a n 6 9 Simple C ara On arene a a o tte s shedtoni yn tedde messed 6 9 Save C dibrat On MT orman ON spesso nE coud stan E O E AS 6 10 Attach Calibration Information yassesessatsesiveisseastavensaten a veaseeaeiveensereoawenayaacemater umask 6 10 Appendix A Vision for LabVIEW Real Time About Vision for LabVIEW Real Time si icsisscusadsageriededcasarsadencodediedsdvanancaneudngensedsbanncsens A 1 SYSLER COMPONEN o A A 1 Development Syste oasia a a a a a TREN A 1 Deployed oys Cree e ea Maren a a A 2 NI IMAQ and Vision for LabVIEW Real Time Installation ce eecccceeeeeeeees A 2 Image Display in Vision for LabVIEW Real Time eccccccccccccc
73. e pixel Line Draw a line in the image Action Click the initial position and click again at the final position Rectangle Draw a rectangle or square in the image Action Click one corner and drag to the opposite corner Oval Draw an oval or circle in the image Action Click the center position and drag to the required size Polygon Draw a polygon in the image Action Click to place a new vertex and double click to complete the ROI element Freehand Region Draw a freehand region in the image Action Click the initial position drag to the required shape and release the mouse button to complete the shape Annulus Draw an annulus in the image Action Click the center position and drag to the required size Adjust the inner and outer radii and adjust the start and end angle Zoom Zoom in or Zoom out in an image Action Click the image to zoom in Hold down the lt Shift gt key and click to zoom out Pan Pan around an image Action Click an initial position drag to the required position and release the mouse button to complete the pan IMAQ Vision for LabVIEW User Manual 3 2 ni com elef leleh gt r Chapter 3 Making Grayscale and Color Measurements Table 3 1 Tools Palette Functions Continued o ae Line Draw a broken aac in the image Action Click to place a new vertex and double click to complete the ROI element Freehand Line Draw a freehand line in the image Action Click the initial position drag t
74. e previous section 1s not attainable For example to be deterministic a pattern matching routine would have to produce results in the same amount of time for any template on any image regardless of content or size However one of the most important characteristics of determinism limiting execution time 1s achievable as long as a final result is not expected for any given time limit The deterministic condition requires both a lower and upper bound on execution time Algorithms designed to support execution caps are referred to as time bounded When time is exceeded these algorithms return with a timeout error For certain vision algorithms the execution time has relatively small jitter if the input sets are similar For instance pattern matching produces results in roughly the same time when searching for the same pattern in images with common content Therefore many vision applications already contain components that have consistent execution times Running the application on LabVIEW RT enhances the time reliability Unfortunately this execution behavior is dependant on the commonality of the input sets In many applications the input sets are common enough that you can safely predict the execution time by running the application over a large representative set of example images In some cases however getting a representative set of example images may be difficult or a bounded National Instruments Corporation A 5 IMAQ Vision for
75. e template e Very Aggressive Uses the largest step size the most subsampling and only the dominant color from the template to search for the template Use this strategy when the color in the template is almost uniform the template is well contrasted from the background and there National Instruments Corporation 5 23 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks is a good amount of separation between different occurrences of the template in the image This strategy is the fastest way to find templates in an image Decide on the best strategy by experimenting with the different options Use the Search Strategy control to select a search strategy Color Score Weight When you search for a template using both color and shape information the color and shape scores generated during the match process are combined to generate the final color pattern matching score The color score weight determines the contribution of the color score to the final color pattern matching score If the color information of the templates is superior to the shape information of the template set the weight higher For example if you use a weight of 1000 the algorithm finds each match by using both color and shape information and then ranks the matches based entirely on their color scores If the weight is 0 the matches are still found using color and shape information but they are ranked based entirely on their shape sco
76. e template that allow for fast accurate matching However you can train the pattern matching algorithm offline and save the RE template image using the IMAQ Write Image and Vision Info VI Machine Vision Searching and Matching Defining a Search Area Two equally important factors define the success of a color pattern matching algorithm accuracy and speed You can define a search area to reduce ambiguity in the search process For example 1f your image has multiple instances of a pattern and only one instance is required for the inspection task the presence of additional instances of the pattern can produce incorrect results To avoid this reduce the search area so that only the required pattern lies within the search area For instance in the fuse box inspection example use the location of the fuses to be inspected to define the search area Because the inspected fuse box may not be in the exact location or have the same orientation in the image as the previous one the search area you define should be large enough to accommodate these variations in the position of the box Figure 5 12 shows how search areas can be selected for different objects National Instruments Corporation 5 21 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks 1 Search Area for 20 Amp Fuses 2 Search Area for 25 Amp Fuses Figure 5 12 Selecting a Search Area for Color Pattern Matching The time required to locate a pattern in
77. e whose corresponding pixels in Image Mask are non zero If an Image Mask pixel is 0 the corresponding Image pixel is not changed Image Mask must be an 8 bit image If you want to apply a processing or analysis function to the entire image do not connect the Image Mask input Connecting the same image to both inputs Image and Image Mask also gives the same effect as leaving the input Image Mask unconnected except in this case the Image must be an 8 bit image IMAQ Vision for LabVIEW User Manual 2 4 ni com Chapter 2 Getting Measurement Ready Images Image Filling The following connector pane applies to VIs performing an operation that fills an image Image Image Out Farameters Examples of this type of operation include reading a file acquiring an image from an IMAQ device or transforming a 2D array into an image This type of VI can modify the size of an image Image Processing The following connector pane applies to VIs that process an image Image Sre Image Dst Image Dst Dut Parameters This connector is the most common type in IMAQ Vision The Image Src input receives the image to process The Image Dst input can receive either another image or the original depending on your goals If two different images are connected to the two inputs the original Image Src image is not modified As shown in the following diagrams if the Image Dst and Image Src inputs receive the same image or if nothing is connec
78. ecution VI A 8 IMAQ Stop VI 2 7 IMAQ Threshold VI 4 1 IMAQ Uninitialize Timed Execution VI A 9 IMAQ UserLookup VI 2 14 4 2 IMAQ Video Out Display Mode VI A 4 A 13 IMAQ Vision Control 1 1 IMAQ Vision for LabVIEW creating applications general steps figure 1 7 inspection steps figure 1 8 function palettes Image Processing 1 4 Machine Vision 1 5 Vision Utilities 1 2 overview I 1 IMAQ Vision for LabVIEW User Manual Index IMAQ Vision Remote Server VI A 10 IMAQ WindClose VI 2 9 IMAQ WindDraw VI 2 8 A 3 A 4 A 10 IMAQ WindLastEvent VI 2 12 IMAQ WindMove VI 2 8 IMAQ WindSetup VI 2 8 IMAQ WindToolsClose VI 3 4 IMAQ WindToolsMove VI 3 4 IMAQ WindToolsSelect VI 3 4 IMAQ WindToolsSetup VI 3 4 IMAQ WindToolsShow VI 3 4 IMAQ Write Image and Vision Info VI 5 15 5 21 5 33 instrument drivers xiii 1 3 2 2 A 1 A 2 NI resources B 1 instrument reader measurements 5 27 K KnowledgeBase B 1 L LabVIEW Real Time Module xiii A 1 learning calibration information choosing learning algorithm 6 6 choosing ROI 6 6 correction table 6 8 learning score and error map 6 7 scaling mode 6 8 voiding calibration 6 9 learning color information choosing color representation sensitivity 3 15 entire image 3 13 ignoring learned colors 3 16 multiple regions in image 3 14 region in image 3 14 specifying information to learn 3 13 lines finding points along edge 5 9 locating objects to in
79. ed version of the binary image as an image mask to the intensity measurement function If you want to make color comparisons convert the binary image ae into an ROI descriptor using the IMAQ MaskToROI VI Vision Utilities Region of Interest Measure Grayscale Statistics You can measure grayscale statistics in images using light meters or quantitative analysis functions You can obtain the center of energy for an image with the centroid function Use the IMAQ Light Meter Point VI Machine Vision Measure Intensities to measure the light intensity at a point in the image Use the IMAQ Light Meter Line VI Machine Vision Measure Intensities to get the pixel value statistics along a line in the image mean intensity standard deviation minimum intensity and maximum intensity Use the IMAQ Light Meter Rectangle VI Machine Vision Measure Intensities to get the pixel value statistics within a rectangular region in an image a a Se Use the IMAQ Quantify VI Image Processing Analysis to obtain the following statistics about the entire image or individual regions in the image mean intensity standard deviation minimum intensity maximum intensity area and the percentage of the image that you analyzed You can specify regions in the image with a labeled image mask A labeled image mask is a binary image that has been processed so that each region in the gt image mask has a unique intensity value Use the IMAQ Label
80. ere in the test image but cannot be rotated or scaled Applies a succession of thinning operations to an object until its width becomes one pixel Blurs an image by attenuating variations of light intensity in the neighborhood of a pixel An edge detection algorithm that extracts the contours in gray level values using a 3 x 3 filter kernel IMAQ Vision for LabVIEW User Manual Glossary spatial calibration spatial filters spatial resolution square function square root function standard representation structuring element subpixel analysis T template threshold threshold interval TIFF time bounded tools palette IMAQ Vision for LabVIEW User Manual Assigns physical dimensions to the area of a pixel in an image Alter the intensity of a pixel relative to variations in intensities of its neighboring pixels You can use these filters for edge detection image enhancement noise reduction smoothing and so forth The number of pixels in an image in terms of the number of rows and columns in the image See exponential function See logarithmic function Contains the low frequency information at the corners and high frequency information at the center of an FFT transformed image A binary mask used in most morphological operations A structuring element is used to determine which neighboring pixels contribute in the operation Finds the location of the edge coordinates in terms of fractions of a
81. ering or particle analysis VIs on the image refer to their help topics in the IMAQ Vision for LabVIEW Help for information about the appropriate border size for the image The default border size is three pixels When you create an image IMAQ Vision creates an internal image structure to hold properties of the image such as its name and border size However no memory is allocated to store the image pixels at this time IMAQ Vision VIs automatically allocate the appropriate amount of memory when the image size is modified For example VIs that acquire or resample an image alter the image size so they allocate the appropriate memory space for the image pixels The output of IMAQ Create is a reference to the image structure Supply this reference as an input to all subsequent IMAQ Vision functions During development you may want to examine the contents of your image at run time With LabVIEW 7 0 or later you can use a LabVIEW image probe to view the contents of your image during execution To create a probe right click on the image wire and select Probe Most VIs belonging to the IMAQ Vision library require an input of one or more image references The number of image references a VI takes depends on the image processing function and the type of image you want to use IMAQ Vision VIs that analyze the image but do not modify the contents require the input of only one image reference VIs that process the contents of images may require a refe
82. erminism when the time to execute the algorithm is predictable and repeatable given any valid input set Executing a deterministic algorithm takes a predetermined amount of time within a prescribed variance IMAQ Vision for LabVIEW User Manual A 4 ni com Appendix A Vision for LabVIEW Real Time Determinism is a product of both the algorithm and the system on which it executes Real time systems such as LabVIEW RT provide the foundation for you to deterministically execute algorithms However determinism is not guaranteed without resource management in any real time system that has dynamically controlled resources Resource contention the inability of a process to access needed resources immediately during execution destroys determinism Examples of resource contention in a vision application include the following e Parallel processes that use the same image e Vision algorithms that allocate memory even for internal workspace from the systems memory manager Resource contention is just one example of how to destroy determinism Determinism also can be destroyed by the nature of some algorithms by adding file I O or by networking Refer to the LabVIEW Real Time Module User Manual for a discussion on determinism and programming deterministic applications Determinism versus Time Bounded Execution Due to the complexity of vision algorithms and the dramatic variance in their input sets mostly images determinism as defined in th
83. es The number of values a pixel can take on which is the number of colors or shades that you can see in the image IMAQ Vision for LabVIEW User Manual Glossary image display environment image enhancement image file image format image mask image palette image processing image source imaging IMAQ inner gradient inspection inspection function instrument driver A window or control that displays an image The process of improving the quality of an image that you acquire from a sensor in terms of signal to noise ratio image contrast edge definition and so on A file containing pixel data and additional information about the image Defines how an image is stored in a file Usually composed of a header followed by the pixel data A binary image that isolates parts of a source image for further processing A pixel in the source image 1s processed if its corresponding mask pixel has a nonzero value A source pixel whose corresponding mask pixel has a value of 0 is left unchanged The gradation of colors used to display an image on screen usually defined by a CLUT Encompasses various processes and analysis functions that you can apply to an image The original input image Any process of acquiring and displaying images and analyzing image data Image Acquisition Finds the inner boundary of objects The process by which parts are tested for simple defects such as missing parts or cracks on p
84. es 4 Measurement Area Figure 5 2 Coordinate Systems of a Reference Image and Inspection Image b If you use IMAQ Find CoordSys 2 Rects specify two rectangular ROIs each containing one separate straight boundary of the object as shown in Figure 5 3 The boundaries cannot be parallel The regions must be large enough to include the boundaries in all the images you want to inspect IMAQ Vision for LabVIEW User Manual 5 4 ni com Chapter 5 Performing Machine Vision Tasks 1 Primary Search Area 3 Origin of the Coordinate System 2 Secondary Search Area 4 Measurement Area Figure 5 3 Locating Coordinate System Axes with Two Search Areas Choose the parameters you need to locate the edges on the object Choose the coordinate system axis direction Choose the results that you want to overlay onto the image ee a Choose the mode for the VI To build a coordinate transformation for the first time set mode to Find Reference To update the coordinate transformation in subsequent images set this mode to Update Reference National Instruments Corporation 5 5 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks Using Pattern Matching to Build a Coordinate Transformation You can build a coordinate transformation using pattern matching Use the IMAQ Find CoordSys Pattern 2 VI Machine Vision Coordinate Systems to define a reference coordinate system based on the location of a reference feature Use t
85. es in the image Use these VIs to find edges along a line a set of parallel lines defined inside a rectangular region rake a set of parallel concentric lines defined inside an annular region concentric rake or a set of radial lines defined inside an annular region spoke You also can use these VIs to find pairs of edges in the image that satisfy certain criteria Analytic Geometry A group of VIs that perform analytic geometry computations on a set of points in an image Use these VIs to fit lines circles and ellipses to a set of points in the image compute the area of a polygon represented by a set of points measure distances between points and find angles between lines represented by points VIs in this subpalette also perform computations such as finding the intersection point of two lines and finding the line bisecting the angle formed by two lines OCR A group of VIs that perform optical character recognition in a region of the image Classification A group of VIs that classify binary objects according to their shape or any user defined feature vector Instrument Readers A group of VIs that accelerate the development of applications that require reading from seven segment displays meters gauges 1D barcodes or 2D barcodes IMAQ Vision Applications Figures 1 1 and 1 2 illustrate the steps for creating an application with IMAQ Vision Figure 1 1 describes the general steps to designing an IMAQ Vision application
86. et to Indirect If you define a coordinate system yourself carefully consider the needs of your application e Express the origin in pixels Always choose an origin location that lies within the calibration grid so that you can convert the location to real world units e Specify the angle as the angle between the x axis of the new coordinate system x and the top row of dots x as shown in Figure 6 4 If your imaging system exhibits nonlinear distortion you cannot visualize the angle as you can in Figure 6 4 because the dots do not appear in straight lines IMAQ Vision for LabVIEW User Manual 6 4 ni com Chapter 6 Calibrating Images 1 Default Origin in a Calibration Grid Image 2 User Defined Origin Figure 6 4 Defining a Coordinate System Learning Calibration Information After you define a calibration grid and reference axis acquire an image of the grid using the current imaging setup Refer to the Acquire or Read an Image section of Chapter 2 Getting Measurement Ready Images for information about acquiring images The grid does not need to occupy the entire image You can choose a region within the image that contains the grid After you acquire an image of the grid learn the calibration information by inputting the image of the grid and the real world distances Ta between the dots into the IMAQ Learn Calibration Template VI Vision a Utilities Calibration Kp Note If you want to specify a list of points instead of a
87. forming Machine Vision Tasks IMAQ Clamp Horizontal Min Machine Vision Measure Distances IMAQ Clamp Vertical Max Machine Vision Measure Distances IMAQ Clamp Vertical Min Machine Vision Measure Distances IMAQ Find Pattern Machine Vision Find Patterns IMAQ Count Object Machine Vision Count and Measure Objects IMAQ Find CoordSys Rect Machine Vision Coordinate Systems IMAQ Find CoordSys 2 Rects Machine Vision Coordinate Systems IMAQ Find CoordSys Pattern Machine Vision Coordinate Systems The following list contains the kinds of information you can overlay on the above VIs Search area input into the VI Search lines used for edge detection Edges detected along the search lines Bounding rectangle of particles Center of particles Result of the VI Select the information you want to overlay by enabling the corresponding Boolean control of the VI Use the IMAQ Clear Overlay VI Vision Utilities Overlay to clear any previous overlay information from the image Use the IMAQ Write Image and Vision Info VI Vision Utilities Overlay to save an image with its overlay information to a file You can read the information from the file into an image using the IMAQ Read Image and Vision Info VI Vision Utilities Overlay Ky Note As with calibration information overlay information is removed from an image when the image size or orientation changes National Instruments Corporation 5 33 IMAQ Visi
88. function National Instruments Corporation G 1 One dimensional Two dimensional Three dimensional The National Instruments internal image file format used for saving complex images and calibration information associated with an image AIPD images have the file extension APD The process by which a machine vision application determines the location orientation and scale of a part being inspected The channel used to code extra information such as gamma correction about a color image The alpha channel is stored as the first byte in the four byte representation of an RGB pixel 1 A rectangular portion of an acquisition window or frame that is controlled and defined by software 2 The size of an object in pixels or user defined units The image operations multiply divide add subtract and modulo An ordered indexed set of data elements of the same type A function that uses dual combinations of opening and closing operations to smooth the boundaries of objects Bit One binary digit either 0 or 1 Byte Eight related bits of data an 8 bit binary number Also denotes the amount of memory required to store one byte of data IMAQ Vision for LabVIEW User Manual Glossary barycenter binary image binary morphology binary threshold bit depth blurring BMP border function brightness buffer The grayscale value representing the centroid of the range of an image s grayscale values in the ima
89. g VIs Vision Utilities Overlay to overlay search regions inspection results and other information such as text and bitmaps IMAQ Overlay Points Overlays points on an image Specify a point by its x coordinate and y coordinate IMAQ Overlay Line Overlays a line on an image Specify a line by its start and end points IMAQ Overlay Multiple Lines Overlays multiple lines on an image IMAQ Overlay Rectangle Overlays a rectangle on an image IMAQ Overlay Oval Overlays an oval or a circle on the image IMAQ Overlay Arc Overlays an arc on the image IMAQ Overlay Bitmap Overlays a bitmap on the image IMAQ Overlay Text Overlays text on an image IMAQ Overlay ROI Overlays an ROI described by the ROI Descriptor on an image To use these VIs pass in the image on which you want to overlay information and the information that you want to overlay Tip You can select the color of the overlays using the previous VIs You can configure the following processing VIs to overlay different types of information about the inspection image IMAQ Find Vertical Edge Machine Vision Locate Edges IMAQ Find Horizontal Edge Machine Vision Locate Edges IMAQ Find Circular Edge Machine Vision Locate Edges IMAQ Find Concentric Edge Machine Vision Locate Edges IMAQ Clamp Horizontal Max Machine Vision Measure Distances 5 32 ni com t El Le ped Hee E gt i E Efi a od HLT Chapter 5 Per
90. ge The histogram of a reversed image is equal to the original histogram flipped horizontally around the center of the histogram In LabVIEW a histogram that can be wired directly into a graph Locates objects in the image similar to the pattern defined in the structuring element A color encoding scheme in hue saturation and intensity A color encoding scheme using hue saturation and luminance information where each image in the pixel is encoded using 32 bits eight bits for hue eight bits for saturation eight bits for luminance and eight unused bits A color encoding scheme in hue saturation and value Represents the dominant color of a pixel The hue function is a continuous function that covers all the possible colors generated using the R G and B primaries See also RGB Hertz Frequency in units of 1 second Input output The transfer of data to from a computer system involving communications channels operator interface devices and or data acquisition and control interfaces A 2D light intensity function f x y where x and y denote spatial coordinates and the value f at any point x y is proportional to the brightness at that point A user defined region of pixels surrounding an image Functions that process pixels based on the value of the pixel neighbors require image borders An image that contains thumbnails of images to analyze or process in a vision application A memory location used to store imag
91. ge histogram An image in which the objects usually have a pixel intensity of 1 or 255 and the background has a pixel intensity of 0 Functions that perform morphological operations on a binary image The separation of an image into objects of interest assigned pixel values of 1 and background assigned pixel values of 0 based on the intensities of the image pixels The number of bits n used to encode the value of a pixel For a given n a pixel can take 2 different values For example if n equals 8 a pixel can take 256 different values ranging from 0 to 255 If n equals 16 a pixel can take 65 536 different values ranging from 0 to 65 535 or 32 768 to 32 767 Reduces the amount of detail in an image Blurring can occur when the camera lens is out of focus or when an object moves rapidly in the field of view You can blur an image intentionally by applying a lowpass frequency filter Bitmap An image file format commonly used for 8 bit and color images BMP images have the file extension BMP Removes objects or particles in a binary image that touch the image border 1 A constant added to the red green and blue components of a color pixel during the color decoding process 2 The perception by which white objects are distinguished from gray and light objects from dark objects Temporary storage for acquired data IMAQ Vision for LabVIEW User Manual G 2 ni com C caliper CAN center of mass chrom
92. hing objects IMAQ Separation is an advanced VI that separates particles without modifying their shapes However erosion and open operations alter the shape of all the particles Kp Note A separation is a time intensive operation compared to an erosion or open operation Consider using an erosion if speed is an issue in your application Improving Particle Shapes al Use the IMAQ FillHoles VI Image Processing Morphology to fill a holes in the particles Use the IMAQ Morphology VI Image Processing Morphology to perform a variety of operations on the particles You can H use the Open Close POpen PClose and AutoM operations to smooth the boundaries of the particles Open and POpen smooth the boundaries of the particle by removing small isthmuses while Close widens the isthmuses Close and PClose fill small holes in the particle AutoM removes isthmuses and fills holes Refer to Chapter 9 Binary Morphology of the IMAQ Vision Concepts Manual for more information about these operations Make Particle Measurements After you create a binary image and improve it you can make particle measurements IMAQ Vision can return the measurements in uncalibrated pixels or calibrated real world units With these measurements you can determine the location of particles and their shape features Use the following VIs to perform particle measurements PR e IMAQ Particle Analysis Report Image Processing Analysis This VI returns the number
93. his technique when the object under inspection does not have straight distinct edges Complete the following steps to build a coordinate transformation using pattern matching Kp Note The object can rotate 360 in the image using this technique if you use rotation invariant pattern matching 1 Define a template that represents the part of the object that you want to use as a reference feature Refer to the Find Measurement Points section for information about defining a template 2 Define a rectangular search area in which you expect to find the template 3 Choose the Match Mode Select Rotation Invariant when you expect your template to appear rotated in the inspection images Otherwise select Shift Invariant Choose the results that you want to overlay onto the image Choose the mode for the VI To build a coordinate transformation for the first time set mode to Find Reference To update the coordinate transformation in subsequent images set this mode to Update Reference Choosing a Method to Build the Coordinate Transformation The flowchart in Figure 5 4 guides you through choosing the best method for building a coordinate transformation for your application IMAQ Vision for LabVIEW User Manual 5 6 ni com Chapter 5 Performing Machine Vision Tasks Object positioning accuracy better than 65 degrees The object under inspection has a straight distinct edge main axis The object contains a second distinct edge
94. ift invariant matching is faster than rotation invariant matching Minimum Contrast The pattern matching algorithm ignores all image regions in which contrast values fall below a set minimum contrast value Contrast is the difference between the smallest and largest pixel values in a region Set the Minimum Contrast control to slightly below the contrast value of the search area with the lowest contrast You can set the minimum contrast to potentially increase the speed of the pattern matching algorithm If the search image has high contrast overall but contains some low contrast regions set a high minimum contrast value to exclude all areas of the image with low contrast Excluding these areas significantly reduces the area in which the pattern matching algorithm must search However If the search image has low contrast throughout set a low minimum contrast to ensure that the pattern matching algorithm looks for the template in all regions of the image Rotation Angle Ranges If you know that the pattern rotation is restricted to a certain range for example between 15 and 15 provide this restriction information to the pattern matching algorithm in the Rotation Angle Ranges control This information improves your search time because the pattern matching algorithm looks for the pattern at fewer angles Refer to Chapter 12 National Instruments Corporation 9 17 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Mach
95. ild a coordinate transformation are the origin angle and axes direction of the coordinate system Some machine vision VIs take this output and adjust the regions of inspection automatically You also can use these outputs to move the regions of inspection relative to the object programmatically Using Edge Detection to Build a Coordinate Transformation You can build a coordinate transformation using two edge detection 2 i techniques Use the IMAQ Find CoordSys Rect VI Machine Vision Coordinate Systems to define a reference coordinate system using one rectangular region Use the IMAQ Find CoordSys 2 Rects VI Machine i Vision Coordinate Systems to define a reference coordinate system using two independent rectangular regions Complete the following steps to build a coordinate transformation using edge detection Ky Note To use these techniques the object cannot rotate more than 65 in the image 1 Specify one or two rectangular regions a If you use IMAQ Find CoordSys Rect specify one rectangular ROI that includes part of two straight nonparallel boundaries of the object as shown in Figure 5 2 This rectangular region must be large enough to include these boundaries in all the images you want to inspect National Instruments Corporation 5 3 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks 1 Search Area for the Coordinate System 3 Origin of the Coordinate System 2 Object Edg
96. image should be six to 10 pixels e The center to center distance between dots in the acquired image should range from 18 to 32 pixels as shown in Figure 6 1 e The minimum distance between the edges of the dots in the acquired image should be six pixels as shown in Figure 6 1 1 Center to Center Distance 2 Center of Grid Dots 3 Distance Between Dot Edges Figure 6 1 Defining a Calibration Grid IMAQ Vision for LabVIEW User Manual 6 2 ni com Chapter 6 Calibrating Images ng Note Click Start Programs National Instruments Vision Documentation Calibration Grid to use the calibration grid installed with IMAQ Vision The dots have radii of 2 mm and center to center distances of 1 cm Depending on your printer these measurements may change by a fraction of a millimeter You can purchase highly accurate calibration grids from optics suppliers such as Edmund Industrial Optics Defining a Reference Coordinate System To express measurements in real world units you need to define a io coordinate system in the image of the grid Use the Calibration Axis Info o control of the IMAQ Set Simple Calibration VI Vision Utilities Ta Calibration to define a coordinate system by its origin angle and axis a direction The origin expressed in pixels defines the center of your coordinate system The angle specifies the orientation of your coordinate system with respect to the angle of the topmost row of dots in the grid image The
97. in which you select an ROI This modal window called an ROI constructor stops the execution of your application until the user either selects an ROI or clicks Cancel to exit the window The ROI constructor is convenient because it saves you the effort of writing code that behaves similarly If you want to customize the behavior of the ROI constructor more than is possible with the IMAQ ConstructROI VI use the Image Display control or the external display window to implement your own ROI constructor IMAQ Vision for LabVIEW User Manual 3 4 ni com Chapter 3 Making Grayscale and Color Measurements Complete the following steps to invoke an ROI constructor and define an ROI from within the ROI constructor window ar 1 Use the IMAQ ConstructROI VI Vision Utilities Region of z Interest to display an image and the tools palette in an ROI constructor window as shown in Figure 3 2 Er l ROI Constructor A a 8 Bit Image a 425 w 1 365 204 4 116 a F Cancel Figure 3 2 ROI Constructor 2 Select an ROI tool from the tools palette Draw an ROI on your image Resize and reposition the ROI until it designates the area you want to inspect 4 Click OK to output a descriptor of the region you selected You can input the ROI descriptor into many analysis and processing functions You also can convert the ROI descriptor into an image mask which you can use to process selected regions in the image Use the VE IMAQ
98. inary morphology or advanced binary morphology to remove unwanted particles separate connected particles or improve the shape of particles Primary morphology functions work on the image as a whole by processing pixels individually Advanced morphology operations are built upon the primary morphological operators and work on particles as a whole as opposed to individual pixels Refer to Chapter 9 Binary Morphology of the IMAQ Vision Concepts Manual for lists of which morphology functions are primary and which are advanced IMAQ Vision for LabVIEW User Manual 4 2 ni com Chapter 4 Performing Particle Analysis The advanced morphology functions require that you specify the type of connectivity to use Connectivity specifies how IMAQ Vision determines if two adjacent pixels belong to the same particle Use connectivity 4 when you want IMAQ Vision to consider pixels to be part of the same particle only when the pixels touch along an adjacent edge Use connectivity 8 when you want IMAQ Vision to consider pixels to be part of the same particle even if the pixels touch only at a corner Refer to Chapter 9 Binary Morphology of the IMAQ Vision Concepts Manual for more information about connectivity Kp Note Use the same type of connectivity throughout your application Removing Unwanted Particles rt Use the IMAQ RejectBorder VI Image Processing Morphology to m remove particles that touch the border of the image Reject particles on the border
99. ine Vision Tasks Pe Pattern Matching of the IMAQ Vision Concepts Manual for information about pattern matching Testing the Search Algorithm on Test Images To determine if your selected template or reference pattern is appropriate for your machine vision application test the template on a few test images by using the IMAQ Match Pattern 2 VI Machine Vision Searching and Matching These test images should reflect the images generated by your machine vision application during true operating conditions If the pattern matching algorithm locates the reference pattern in all cases you have selected a good template Otherwise refine the current template or select a better template until both training and testing are successful Using a Ranking Method to Verify Results The manner in which you interpret the IMAQ Match Pattern 2 results depends on your application For typical alignment applications such as finding a fiducial on a wafer the most important information is the position and location of the best match Use the Position and Bounding Box elements of the Matches indicator to get the position and location of a match In inspection applications such as optical character verification OCV the score of the best match is more useful The score of a match returned by the pattern matching algorithm is an indicator of the closeness between the original pattern and the match found in the image A high score indicates a very close match
100. ing skeleton function smoothing filter Sobel filter National Instruments Corporation G 15 Glossary Region of interest 1 An area of the image that is graphically selected from a window displaying the image This area can be used focus further processing 2 A hardware programmable rectangular portion of the acquisition window A collection of tools that enable you to select a region of interest from an image These tools let you select points lines annuli polygons rectangles rotated rectangles ovals and freehand open and closed contours The amount by which one image is rotated relative to a reference image This rotation is computed relative to the center of the image A pattern matching technique in which the reference pattern can be located at any orientation in the test image as well as rotated at any degree An object in an image that you want to classify The amount of white added to a pure color Saturation relates to the richness of a color A saturation of zero corresponds to a pure color with no white added Pink is a red with low saturation A pattern matching technique in which the reference pattern can be any size in the test image Fully partitions a labeled binary image into non overlapping segments with each segment containing a unique particle Separates particles that touch each other by narrow isthmuses A pattern matching technique in which the reference pattern can be located anywh
101. ing environment and need to create machine vision and image processing applications using LabVIEW VIs The manual guides you through tasks beginning with setting up your imaging system to taking measurements It also describes how to create a real time vision application using IMAQ Vision with the LabVIEW Real Time RT Module The following conventions appear in this manual The symbol leads you through nested menu items and dialog box options to a final action The sequence File Page Setup Options directs you to pull down the File menu select the Page Setup item and select Options from the last dialog box This icon denotes a tip which alerts you to advisory information This icon denotes a note which alerts you to important information Bold text denotes items that you must select or click in the software such as menu items and dialog box options Bold text also denotes parameter names Italic text denotes variables emphasis a cross reference or an introduction to a key concept This font also denotes text that is a placeholder for a word or value that you must supply Text in this font denotes text or characters that you should enter from the keyboard sections of code programming examples and syntax examples This font is also used for the proper names of disk drives paths directories programs subprograms subroutines device names functions operations variables filenames and extensions Bold text in this font
102. ing Edge Detection Discontinuities in an image typically represent abrupt changes in pixel intensity values which characterize the boundaries of objects Use the edge detection tools to identify and locate sharp discontinuities in an image Finding Lines or Circles If you want to find points along the edge of an object and find a line describing the edge use the IMAQ Find Vertical Edge IMAQ Find Horizontal Edge and IMAQ Find Concentric Edge VIs Machine Vision Locate Edges IMAQ Find Vertical Edge and IMAQ Find Horizontal Edge find edges based on rectangular search areas as shown in Figure 5 5 Wi IMAQ Find Concentric Edge finds edges based on annular search areas i g i National Instruments Corporation 5 9 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks 1 Search Region 3 Detected Edge Points 2 Search Lines 4 Line Fit to Edge Points Figure 5 5 Finding a Straight Feature If you want to find points along a circular edge and find the circle that best fits the edge as shown in Figure 5 6 use the IMAQ Find Circular Edge VI Machine Vision Locate Edges IMAQ Vision for LabVIEW User Manual 5 10 ni com Chapter 5 Performing Machine Vision Tasks 1 Annular Search Region 3 Detected Edge Points 2 Search Lines 4 Circle Fit To Edge Points Figure 5 6 Finding a Circular Feature IMAQ Find Vertical Edge IMAQ Find Horizontal Edge and IMAQ Find Concentric Edge locate the intersection
103. ints based on their contrast and slope You can specify if you want to find the edge points using subpixel accuracy Finding Edge Points Along Multiple Search Contours Use the IMAQ Rake IMAQ Spoke and IMAQ Concentric Rake VIs Machine Vision Caliper to find edge points along multiple search contours These functions behave like the IMAQ Edge Tool VI but they find edges on multiple contours Pass in an ROI descriptor to define the search region for these VIs IMAQ Rake works on a rectangular search region The search lines are drawn parallel to the orientation of the rectangle Control the number of search lines in the region by specifying the distance in pixels between each line Specify the search direction as left to right or right to left for a horizontally oriented rectangle Specify the search direction as top to bottom or bottom to top for a vertically oriented rectangle IMAQ Spoke works on an annular search region scanning the search lines that are drawn from the center of the region to the outer boundary and that fall within the search area Control the number of lines in the region by specifying the angle in degrees between each line Specify the search direction as either going from the center outward or from the outer boundary to the center IMAQ Concentric Rake works on an annular search region The concentric rake is an adaptation of the rake to an annular region Edge detection is performed along search lines that occu
104. ion VI A 8 IMAQ Clamp Horizontal Max VI 5 26 5 32 IMAQ Clamp Horizontal Min VI 5 26 5 33 IMAQ Clamp Vertical Max VI 5 26 5 33 IMAQ Clamp Vertical Min VI 5 26 5 33 IMAQ Classify VI 5 28 IMAQ Clear Overlay VI 5 33 IMAQ Close VI 2 7 IMAQ ColorLearn VI 3 12 3 15 IMAQ ColorMatch VI 3 12 IMAQ ColorThreshold VI 4 2 IMAQ ColorToRGB VI 3 12 IMAQ ComplexAttenuate VI 2 17 IMAQ ComplexImageToArray VI 2 18 IMAQ ComplexPlaneToImage VI 2 18 IMAQ ComplexTruncate VI 2 17 IMAQ Concentric Rake VI 5 12 IMAQ ConstructROI VI 3 5 IMAQ Convert Annulus to ROI VI 3 8 IMAQ Convert Line to ROI VI 3 8 IMAQ Convert Pixel to Real World VI 5 25 IMAQ Convert Point to ROI VI 3 8 IMAQ Convert Rectangle to ROI Polygon VI 3 8 IMAQ Convert Rectangle to ROI VI 3 8 IMAQ Convert ROI to Annulus VI 3 8 IMAQ Convert ROI to Line VI 3 8 IMAQ Convert ROI to Point VI 3 8 IMAQ Convert ROI to Rectangle VI 3 8 IMAQ Convolute VI 2 15 IMAQ Count Object VI 5 33 IMAQ Create VI 2 2 IMAQ Dispose Classifier VI 5 28 IMAQ Dispose VI note 2 3 IMAQ Vision for LabVIEW User Manual 4 IMAQ Draw Text VI A 11 IMAQ Draw VI A 11 A 12 IMAQ Edge Tool VI 2 14 5 11 IMAQ Equalize VI 2 14 IMAQ ExtractColorPlanes VI 3 10 3 11 IMAQ ExtractSingleColorPlane VI 3 11 IMAQ FFT VI 2 16 IMAQ FillHoles VI 4 4 IMAQ Find Circular Edge VI 5 10 5 32 IMAQ Find Concentric Edge VI 5 9 5 32 IMAQ Find CoordSys 2 Rects V
105. ion preserves all of the zero frequency information Zero frequency information corresponds to the DC component of the image or the average intensity of the image in the spatial domain e Highpass attenuation The amount of attenuation is inversely proportional to the frequency information At high frequencies there is little attenuation As the frequencies decrease the attenuation increases The zero frequency component is removed entirely e Lowpass truncation Frequency components above the ideal cutoff frequency are removed and the frequencies below it remain unaltered e Highpass truncation Frequency components above the ideal cutoff frequency remain unaltered and the frequencies below it are removed 3 To transform your image back to the spatial domain use the F IMAQ InverseFFT VI Image Processing Frequency Domain National Instruments Corporation 2 17 IMAQ Vision for LabVIEW User Manual Chapter 2 Getting Measurement Ready Images Advanced Operations The IMAQ ImageToComplexPlane VI Image Processing Frequency Paha a Domain and IMAQ ComplexPlaneToImage VI Image Processing Bro Frequency Domain allow you to access process and update n independently the magnitude phase real and imaginary planes of a complex image You also can convert a complex image to an array and a back with the IMAQ ComplexImageToArray VI Image Processing Frequency Domain and IMAQ ArrayToComplexImage VI Image T Processing
106. itive to changes in rotation than one that is rotationally asymmetric National Instruments Corporation 5 19 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks hn 8G Feature Detail A template with relatively coarse features is less sensitive to variations in size and rotation than a model with fine features However the model must contain enough detail to identify it Positional Information A color template whose luminance plane contains strong edges in both the x and y directions is easier to locate Background Information Unique background information in a template improves search performance and accuracy during the grayscale pattern matching phase This requirement could conflict with the color information requirement of color pattern matching because background colors may interfere with the color location phase Avoid this problem by choosing a template with sufficient background information for grayscale pattern matching while specifying the exclusion of the background color during the color location phase Refer to the Training the Color Pattern Matching Algorithm section of this chapter for more information about how to ignore colors Training the Color Pattern Matching Algorithm After you have created a good template image the color pattern matching algorithm needs to learn the important features of the template The learning process depends on the type of matching that you expect to
107. l value as well as the pixel values of its neighbors The sum of this calculation is divided by the sum of the elements in the matrix to obtain a new pixel value Increases the brightness and contrast in dark regions of an image and decreases the contrast in bright regions of the image The image operations AND NAND OR XOR NOR XNOR difference mask mean max and min Compression in which the decompressed image is identical to the original image Compression in which the decompressed image is visually similar but not identical to the original image Applies a linear attenuation to the frequencies in an image with no attenuation at the lowest frequency and full attenuation at the highest frequency Removes or attenuates high frequencies present in the FFT domain of an image Attenuates intensity variations in an image You can use these filters to smooth an image by eliminating fine details and blurring edges Attenuates high frequencies present in the frequency domain of the image A lowpass frequency filter suppresses information related to fast variations of light intensities in the spatial image Removes all frequency information above a certain frequency Uses an L shaped structuring element in the skeleton function The brightness information in the video picture The luma signal amplitude varies in proportion to the brightness of the video signal and corresponds exactly to the monochrome picture IMAQ Vision for La
108. lay play g panel as shown in Figure 2 1 You can access the Image Display control by right clicking the front panel and selecting Vision Kp Note If your Palette View is set to Express you can access the Image Display control by right clicking the front panel and selecting All Controls Vision National Instruments Corporation 2 9 IMAQ Vision for LabVIEW User Manual Chapter 2 Getting Measurement Ready Images Image 2 1 Display Area 3 ROI Tools Palette 2 Image Information Indicator 4 Scrollbars Figure 2 1 LabVIEW Image Display Control To display an image wire the image output of an IMAQ Vision VI into the image display terminal on the block diagram as shown in Figure 2 2 Figure 2 2 An Image Wired into the Image Display Control Terminal The Image Display control contains the following elements e Display area Displays an image e Image information indicator Displays information about your image and the ROI that you are currently drawing IMAQ Vision for LabVIEW User Manual 2 10 ni com Chapter 2 Getting Measurement Ready Images e ROI tools palette Contains tools for drawing ROIs panning and zooming Unlike external display windows each Image Display control uses its own set of tools e Scrollbars Allows you to position the image in the display area During design time you can customize the appearance of the control by rearranging the control elements configuring properties through the popup menu
109. lgorithm accuracy and speed You can define a search area to reduce ambiguity in the search process For example if your image has multiple instances of a pattern and only one of them is required for the inspection National Instruments Corporation 5 15 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks task the presence of additional instances of the pattern can produce incorrect results To avoid this reduce the search area so that only the required pattern lies within the search area The time required to locate a pattern in an image depends on both the template size and the search area By reducing the search area you can reduce the required search time Increasing the template size can improve the search time but doing so reduces match accuracy if the larger template includes an excess of background information In many inspection applications you have general information about the location of the fiducial Use this information to define a search area For example in a typical component placement application each printed circuit board PCB being tested may not be placed in the same location with the same orientation The location of the PCB9 in various images can move and rotate within a known range of values as illustrated in Figure 5 11 Figure 5 1 1a shows the template used to locate the PCB in the image Figure 5 1 1b shows an image containing a PCB with a fiducial you want to locate Notice the
110. line magazine a product advisor and a community area where you can share ideas questions and source code with vision developers around the world XIV ni com Introduction to IMAQ Vision This chapter describes the IMAQ Vision for LabVIEW software outlines the IMAQ Vision palette organization and lists the steps for making a machine vision application Kp Note Refer to the release notes that came with your software for information about the system requirements and installation procedure for IMAQ Vision for LabVIEW About IMAQ Vision IMAQ Vision for LabVIEW a part of the Vision Development Module is a library of LabVIEW VIs that you can use to develop machine vision and scientific imaging applications The Vision Development Module also includes the same imaging functions for LabWindows CVI and other C development environments as well as ActiveX controls for Visual Basic Vision Assistant another Vision Development Module software product enables you to prototype your application strategy quickly without having to do any programming Additionally NI offers Vision Builder AI configurable machine vision software that you can use to prototype benchmark and deploy applications IMAQ Vision Control Palette Image The Vision control palette is available from the top level of the controls palette in LabVIEW 7 0 or later In LabVIEW 6 x the Vision control palette is available from the user controls palette The Vi
111. lly on one buffer Use the b grab functions for high speed image acquisition Use the acquire IMAQ Grab Setup VI Image Acquisition to start the acquisition b Use the IMAQ Grab Acquire VI Image Acquisition to return a copy Stop of the current image Use the IMAQ Stop VI Image Acquisition er Low Level Acquisition to stop the acquisition e Acquire a fixed number of images using the IMAQ Sequence VI Image Acquisition IMAQ Sequence acquires one image after another until it has acquired the number of images you requested If you want to acquire only certain images supply IMAQ Sequence with a table describing the number of frames to skip after each acquired frame Kp Note When you are finished with the image acquisition you must use the IMAQ Close VI close Image Acquisition to release resources associated with the image acquisition device Ero Use the IMAQ ReadFile VI Vision Utilities Files to open and read data from a file stored on your computer into the image reference You can read from image files stored in a standard format such as BMP TIFF JPEG PNG and AIPD or a nonstandard format you specify In all cases the software automatically converts the pixels it reads into the type of image you pass in Ere Use the IMAQ Read Image and Vision Info VI Vision Utilities Files to open an image file containing additional information such as calibration information template information for pattern matching or overla
112. lowing VIs to convert an ROI contour encoded by an ROI descriptor to a simple description for the contour FOr e IMAQ Convert ROI to Point The output point is specified by its i x and y coordinates A e IMAQ Convert ROI to Line The output line is specified by its start h and end points e IMAQ Convert ROI to Rectangle The output rectangle is specified by its top left point bottom right point and rotation angle e IMAQ Convert ROI to Annulus The output annulus is specified by its center point inner and outer radii and start and end angles IMAQ Vision for LabVIEW User Manual 3 8 ni com Chapter 3 Making Grayscale and Color Measurements Defining Regions with Masks You can define regions to process with image masks An image mask is an 8 bit image of the same size as or smaller than the image you want to process Pixels in the image mask determine if the corresponding pixel in the image to process needs to be processed If a pixel in the image mask has a value different than 0 the corresponding pixel in the image to process is processed If a pixel in the image mask has a value of 0 the corresponding pixel in the image to process is left unchanged Use masks when you need to make intensity measurements on particles in an image First threshold your image to make a new binary image Refer to Chapter 4 Making Grayscale and Color Measurements for information about binary images You can input the binary image or a label
113. lter IMAQ NthOrder Image Processing Filters allows you to define a a lowpass or highpass filter depending on the value of N that you choose One specific Nth order filter the median filter removes speckle noise which appears as small black and white dots Refer to Chapter 5 Image Processing of the IMAQ Vision Concepts Manual for more information about Nth order filters B Grayscale Morphology Perform grayscale morphology when you want to filter grayscale features of an image Grayscale morphology helps you remove or enhance isolated features such as bright pixels on a dark background Use these transformations on a grayscale image to enhance non distinct features before thresholding the image in preparation for particle analysis Grayscale morphological transformations compare a pixel to those pixels surrounding it The transformation keeps the smallest pixel values when performing an erosion or keeps the largest pixel values when performing a dilation National Instruments Corporation 2 15 IMAQ Vision for LabVIEW User Manual Chapter 2 FFT Getting Measurement Ready Images Morph LM Refer to Chapter 5 Image Processing of the IMAQ Vision Concepts Manual for more information about grayscale morphology transformations Use the IMAQ GrayMorphology VI Image Processing Morphology to perform one of the following seven transformations e Erosion Reduces the brightness of pixels that are surrounded by neighb
114. lue RGB intensity An image containing color information usually encoded in the RGB form The mathematical representation for a color For example color can be described in terms of red green and blue hue saturation and luminance or hue saturation and intensity Stores information obtained from the FFT of an image The complex numbers that compose the FFT plane are encoded in 64 bit floating point values 32 bits for the real part and 32 bits for the imaginary part Defines which of the surrounding pixels of a given pixel constitute its neighborhood IMAQ Vision for LabVIEW User Manual Glossary connectivity 4 connectivity 8 contrast convex hull convex hull function convolution convolution kernel D Danielsson function DAQ determinism digital image dilation driver Only pixels adjacent in the horizontal and vertical directions are considered neighbors All adjacent pixels are considered neighbors A constant multiplication factor applied to the luma and chroma components of a color pixel in the color decoding process The smallest convex polygon that can encapsulate a particle Computes the convex hull of objects in a binary image See linear filter 2D matrices or templates used to represent the filter in the filtering process The contents of these kernels are a discrete 2D representation of the impulse response of the filter that they represent Similar to the distance functions
115. mages The selection of a good template image plays a critical part in obtaining good results Because the template image represents the pattern that you want to find make sure that all the important and unique characteristics of the pattern are well defined in the image Several factors are critical in creating a template image These critical factors include symmetry feature detail positional information and background information Symmetry A rotationally symmetric template as shown in Figure 5 7ais less sensitive to changes in rotation than one that is rotationally asymmetric A rotationally symmetric template provides good positioning information but no orientation information National Instruments Corporation 5 13 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks Figure 5 7 Symmetry Feature Detail A template with relatively coarse features is less sensitive to variations in size and rotation than a model with fine features However the model must contain enough detail to identify the feature Figure 5 8 Feature Detail Positional Information A template with strong edges in both the x and y directions is easier to locate Figure 5 9 Positional Information IMAQ Vision for LabVIEW User Manual 5 14 ni com Chapter 5 Performing Machine Vision Tasks Background Information Unique background information in a template improves search performance and accuracy Figure
116. make measurements based on the values obtained by meter and LCD readers National Instruments Corporation Use the IMAQ Get Meter or IMAQ Get Meter 2 VIs Machine Vision Instrument Readers to calibrate a meter or gauge that you want to read IMAQ Get Meter calibrates the meter using the initial position and full scale position of the needle This VI calculates the position of the base of the needle and the arc traced by the tip of the needle IMAQ Get Meter 2 calibrates the meter using three points on the meter the base of the needle the tip of the needle at its initial position and the tip of the needle at its full scale position This VI calculates the position of the points along the arc covered by the tip of the needle Use the IMAQ Read Meter VI Machine Vision Instrument Readers to read the position of the needle using the base of the needle and the array of points on the arc traced by the tip of the needle 5 27 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks e aa Sa Use the IMAQ Get LCD ROI VI Machine Vision Instrument Readers to calculate the ROI around each digit in an LCD or LED To find the area of each digit all the segments of the indicator must be activated Use the IMAQ Read Single Digit VI Machine Vision Instrument Readers to read one digit of an LCD or LED Use the IMAQ Read LCD VI Machine Vision Instrument Readers to read multiple digits of an LC
117. may contend with another piece in LabVIEW for access to the memory manager This could cause it to lose priority to another execution thread To alleviate this problem pre allocate resources during initialization for internal algorithm workspace and the timing mechanism Use the IMAQ Initialize Timed 4a Execution VI Vision Utilities IMAQ RT to preallocate memory used by the IMAQ Vision algorithms Use IMAQ Initialize Timed Execution to initialize the environment Because resource requirements differ among vision applications you can change the amount of memory reserved using the Reserved Memory Size control If the reserved resources are exhausted during execution a special out of memory error message is generated If you receive this error IMAQ Vision for LabVIEW User Manual A 6 ni com Appendix A Vision for LabVIEW Real Time increase the amount of resource memory to meet the needs of your processing The resources you reserve at initialization are not used until the timing mechanism is started These resources are intended for use in internal processing that is not exposed in the LabVIEW environment For objects that are exposed in Lab VIEW always preallocate resources before entering the time bounded portion of your code For example preallocate IMAG destination images using IMAQ Create Vision Utilities Image 2 Management and IMAQ SetImageSize Vision Utilities Image Management before entering time bounded code Prep
118. ms tutorials application notes instrument drivers and so on Free Technical Support All registered users receive free Basic Service which includes access to hundreds of Application Engineers worldwide in the NI Developer Exchange at ni com exchange National Instruments Application Engineers make sure every question receives an answer Training and Certification Visit ni com training for self paced training eLearning virtual classrooms interactive CDs and Certification program information You also can register for instructor led hands on courses at locations around the world System Integration TIf you have time constraints limited in house technical resources or other project challenges National Instruments Alliance Partner members can help To learn more call your local NI office or visit ni com alliance If you searched ni com and could not find the answers you need contact your local office or NI corporate headquarters Phone numbers for our worldwide offices are listed at the front of this manual You also can visit the Worldwide Offices section of ni com niglobal to access the branch office Web sites which provide up to date contact information support phone numbers email addresses and current events National Instruments Corporation B 1 IMAQ Vision for LabVIEW User Manual Glossary Numbers 1D 2D 3D AIPD alignment alpha channel area arithmetic operators array auto median
119. n is a critical factor for your application use a correction table A correction table is a lookup table stored in memory that contains the real world location information of all the pixels in the image The extra memory requirements for this option are based on the size of the image Use this option when you want to correct several images at a time in your vision application Set the Learn Correction Table element of the Calibration Learn Setup control to learn the correction table Setting the Scaling Method Use the Corrected Image Scaling element of the Calibration Learn Setup control to choose the appearance of the corrected image Select either Scale to Fit or Scale to Preserve Area Refer to Chapter 3 System Setup and Calibration of the IMAQ Vision Concepts Manual for more information about the scaling mode IMAQ Vision for LabVIEW User Manual 6 8 ni com Chapter 6 Calibrating Images Calibration Invalidation Any image processing operation that changes the image size or orientation voids the calibration information in a calibrated image Examples of VIs that void calibration information include IMAQ Resample IMAQ Extract IMAQ ArrayTolImage and IMAQ Unwrap Simple Calibration When the axis of your camera is perpendicular to the image plane and lens distortion is negligible use a simple calibration In a simple calibration a pixel coordinate is transformed to a real world coordinate through scaling in the horizontal and ver
120. n that invalidates time constraints If the error cluster is passed between VIs sequentially this type of conflict is avoided Use the error cluster to sequence your VIs and one loop in the code to avoid time constraint conflicts All non vision processing during time bounded execution is not constrained by the timing mechanism increasing the jitter of the overall execution Consequently limit non vision processing during time bounded execution In particular eliminate any operation in LabVIEW RT requesting resources because these operations nullify the time limit For example do not build or resize arrays to sizes determined at run time if a time limit is active However you can perform such operations as reading elements from an array Other operations such as file I O serial I O and networking are inherently non deterministic and should be avoided in the time critical portion of your application Refer to the LabVIEW RT documentation to determine which routines can execute deterministically Because some non vision processing may be required during timed execution use IMAQ Check Timed Execution Vision Utilities IMAQ RT periodically to see if time has expired Determine how frequently you need to check for expired time based on the complexity of the non vision process and the required jitter IMAQ Vision for LabVIEW User Manual A 8 ni com Appendix A Vision for LabVIEW Real Time Closing the Timed Environment xg When time boun
121. nd a coordinate system associated with an object in an image Use these VIs to find the coordinate system using either edge detection or pattern matching You can then use this coordinate system to take measurements from other Machine Vision VIs Count and Measure Objects A VI that thresholds an image to isolate objects from the background and then finds and measures characteristics of the objects This VI also can ignore unwanted objects in the image when making measurements Measure Intensities A group of VIs that measure the intensity of a pixel at a point or the statistics of pixel intensities along a line or rectangular region in an image Measure Distances A group of VIs that measure distances such as the minimum and maximum horizontal distance between two vertically oriented edges or the minimum and maximum vertical distance between two horizontally oriented edges Locate Edges A group of VIs that locate vertical horizontal and circular edges Find Patterns A VI that learns and searches for a pattern in an image 1 5 IMAQ Vision for LabVIEW User Manual Chapter 1 Introduction to IMAQ Vision Ra How to Create IMAQ Vision for LabVIEW User Manual Searching and Matching A group of VIs that create and search for patterns in grayscale and color images This subpalette also contains a VI to search for objects with predefined shapes in binary images Caliper A group of VIs that find edges along different profil
122. nd for you to extract the information you need from the image 2 Position your camera so that it is perpendicular to the object under inspection If your camera acquires images of the object from an angle perspective errors occur Even though you can compensate for these errors with software NI recommends that you use a perpendicular inspection angle to obtain the most accurate results National Instruments Corporation 2 1 IMAQ Vision for LabVIEW User Manual Chapter 2 Getting Measurement Ready Images 3 Select an image acquisition device that meets your needs National Instruments offers several image acquisition IMAQ devices such as analog color and monochrome devices as well as digital devices Visit ni com imaq for more information about IMAQ devices 4 Configure the driver software for your image acquisition device If you have an IMAQ device configure your NI IMAQ driver software through MAX Open MAX by double clicking the Measurement amp Automation Explorer icon on your desktop Refer to the NI IMAQO User Manual and the Measurement amp Automation Explorer Help for IMAQ for more information Calibrate Your Imaging System After you set up your imaging system you may want to calibrate your system to assign real world coordinates to pixel coordinates and compensate for perspective and nonlinear errors inherent in your imaging system Perspective errors occur when your camera axis is not perpendicular to the object
123. ndGetROI VI Vision Utilities External Display to get the user selected ROI for processing on the RT target Programming Errors Why won t my LabVIEW VI run on my RT target Your IMAQ Vision VI may not be supported by the LabVIEW RT The following VIs are among those not supported ae e IMAQ Browser Delete Vision Utilities External Display Browser e IMAQ Browser Focus Vision Utilities External Display Browser HE e IMAQ Browser Focus Setup Vision Utilities External Display Browser e IMAQ Browser Insert Vision Utilities External Display Browser e IMAQ Browser Replace Vision Utilities External Display Browser mez e IMAQ Browser Setup Vision Utilities External Display Browser ai IMAQ Draw Vision Utilities Pixel Manipulation a _ Fa e IMAQ Draw Text Vision Utilities Pixel Manipulation gt National Instruments Corporation A 11 IMAQ Vision for LabVIEW User Manual Appendix A Vision for LabVIEW Real Time 7 e IMAQ WindGrid Vision Utilities External Display e Other obsoleted VIs If your program contains a VI that has been updated or replaced to support new functionality the icon of the obsoleted VI will contain a small black X How can I make my Vision for LabVIEW application work on my RT system if it contains IMAQ Draw or IMAQ Draw Text The IMAQ Draw and IMAQ Draw Text VIs are not supported under the LabVIEW RT However you can achieve similar functionality by using
124. ng process By replacing the second to last component in the color spectrum the black color is ignored during the color matching process To ignore other color components in color matching determine the index to the color spectrum by locating the corresponding bins in the color wheel where each bin corresponds to a component in the color spectrum array Ignoring certain colors such as the background color results in a more accurate color matching score Ignoring the background color also provides more flexibility when defining the regions of interest in the color matching process Ignoring certain colors such as the white color created by glare on a metallic surface also improves the accuracy of the color matching Experiment learning the color information about different parts of the images to determine which colors to ignore Refer to Chapter 14 Color Inspection of the IMAQ Vision Concepts Manual for more information about the color wheel and color bins IMAQ Vision for LabVIEW User Manual 3 16 ni com Performing Particle Analysis This chapter describes how to perform particle analysis on your images Use particle analysis to find statistical information such as the area number location and presence of particles With this information you can perform many machine vision inspection tasks such as detecting flaws on silicon wafers or detecting soldering defects on electronic boards Examples of how particle analysis can help y
125. nnected region or grouping of pixels in an image in which all pixels have the same intensity level A series of processing operations and analysis functions that produce information about the particles in an image The technique used to quickly locate a grayscale template within a grayscale image An element of a digital image Also called pixel Picture element The smallest division that makes up the video scan line For display on a computer monitor a pixel s optimum dimension is square aspect ratio of 1 1 or the width equal to the height The ratio between the physical horizontal and vertical sizes of the region covered by the pixel An acquired pixel should optimally be square thus the optimal value is 1 0 but typically it falls between 0 95 and 1 05 depending on camera quality Directly calibrates the physical dimensions of a pixel in an image The number of bits used to represent the gray level of a pixel IMAQ Vision for LabVIEW User Manual Glossary PNG Prewitt filter proper closing proper opening Q quantitative analysis R real time resolution reverse function RGB RGB U64 Roberts filter Portable Network Graphic An image file format for storing 8 bit 16 bit and color images with lossless compression PNG images have the file extension PNG An edge detection algorithm that extracts the contours in gray level values using a 3 x 3 filter kernel A finite combination of successive cl
126. nt to analyze In the frequency domain the light drift appears as a limited set of low frequencies around the average intensity of the image DC component IMAQ Vision for LabVIEW User Manual 2 16 ni com Chapter 2 Getting Measurement Ready Images You can use algorithms working in the frequency domain to isolate and remove these unwanted frequencies from your image Complete the following steps to obtain an image in which the unwanted pattern has disappeared but the overall features remain 1 Use the IMAQ FFT VI Image Processing Frequency Domain to a convert an image from the spatial domain to the frequency domain This VI computes the FFT of the image and results in a complex image representing the frequency information of your image 2 Improve your image in the frequency domain with a lowpass or highpass frequency filter Specify which type of filter to use with the IMAQ ComplexAttenuate VI Image Processing Frequency Domain or the IMAQ ComplexTruncate VI Image Processing Frequency Domain Lowpass filters smooth noise details textures and sharp edges in an image Highpass filters emphasize details textures and sharp edges in images but they also emphasize noise a amp amp f iia a e Lowpass attenuation The amount of attenuation is directly proportional to the frequency information At low frequencies there is little attenuation As the frequencies increase the attenuation increases This operat
127. ntal Edge Machine Vision Locate Edges IMAQ Find Vertical Edge Machine Vision Locate Edges Annulus IMAQ Find Circular Edge Machine Vision Locate Edges IMAQ Find Concentric Edge Machine Vision Locate Edges S HS lee i pel Mok EP SE ee IMAQ Vision for LabVIEW User Manual 5 8 ni com Chapter 5 Performing Machine Vision Tasks Defining Regions Programmatically When you design an automated application you need to define ROIs programmatically You can programmatically define regions in two ways e Specify the elements of the ROI descriptor e Specify regions by providing basic parameters that describe the region you want to define You can specify a rotated rectangle by providing the coordinates of the top left point and the bottom right point and the rotation angle You can specify an annulus by providing the coordinates of the center inner radius outer radius start angle and end angle You can specify a point by setting its x coordinates and y coordinates You can specify a line by setting the coordinates of the start and end points Refer to Chapter 4 Performing Particle Analysis for more information about defining ROIs Find Measurement Points After you set regions of inspection you can locate points within those regions on which you can base measurements You can locate measurement points using edge detection pattern matching color pattern matching and color location Finding Features Us
128. o compute the distances between consecutive pairs of points in an array of points You can obtain these points from the image using any one of the feature detection methods described in the Find Measurement Points section of this chapter et bey ped Lz S IMAQ Vision for LabVIEW User Manual 5 26 ni com Chapter 5 Performing Machine Vision Tasks Making Analytic Geometry Measurements Use the following VIs Machine Vision Analytic Geometry to make geometrical measurements from the points you detect in the image a e e3 bal f oi EE EH pH EF IMAQ Fit Line Fits a line to a set of points and computes the equation of the line IMAQ Fit Circle 2 Fits a circle to a set of at least three points and computes its area perimeter and radius IMAQ Fit Ellipse 2 Fits an ellipse to a set of at least six points and computes its area perimeter and the lengths of its major and minor axis IMAQ Lines Intersection Finds the angle and point of intersection of two lines specified by their start and end points IMAQ Perpendicular Line Finds the perpendicular line and distance from a point to a line IMAQ Bisecting Line Finds the line that bisects the angle formed by two lines IMAQ Mid Line Finds the line that is midway between a point and a line and is parallel to the line IMAQ Polygon Area Calculates the area of a polygon specified by its vertex points Making Instrument Reader Measurements Use the following VIs to
129. o the required shape and release the mouse button to complete the shape Rotated Rectangle Draw a rotated rectangle in the image Action Click one corner and drag to the opposite corner to create the rectangle Then click the lines inside the rectangle and drag to adjust the rotation angle Hold down the lt Shift gt key when drawing an ROI if you want to constrain the ROI to the horizontal vertical or diagonal axes when possible Use the selection tool to position an ROI by its control points or vertices ROIs are context sensitive meaning that the cursor actions differ depending on the ROI with which you interact For example if you move your cursor over the side of a rectangle the cursor changes to indicate that you can click and drag the side to resize the rectangle If you want to draw more than one ROI in an image display environment hold down the lt Ctrl gt key while drawing additional ROIs Defining Regions Interactively You can interactively define an ROI using the ROI tools palette in three ways with the LabVIEW Image Display control in a separate floating window or as part of an ROI constructor window Defining an ROI in the Image Display Control To define an ROI within the LabVIEW Image Display control select an ROI tool from the tools palette and draw an ROI on your image National Instruments Corporation 3 3 IMAQ Vision for LabVIEW User Manual Chapter 3 Making Grayscale and Color Measurements You
130. of the image when you suspect that the information about those particles is incomplete ax Use the IMAQ RemoveParticle VI Image Processing Morphology to r remove large or small particles that do not interest you You also can use the Erode Open and POpen functions in the IMAQ Morphology VI m Image Processing Morphology to remove small particles Unlike the IMAQ RemoveParticle VI these three functions alter the size and shape of the remaining particles Use the hit miss function of the IMAQ Morphology VI to locate particular configurations of pixels which you define with a structuring element Depending on the configuration of the structuring element the hit miss function can locate single isolated pixels cross shape or longitudinal patterns right angles along the edges of particles and other user specified shapes Refer to Chapter 9 Binary Morphology of the IMAQ Vision Concepts Manual for more information about structuring elements If you know enough about the shape features of the particles you want to BE keep or remove use the IMAQ Particle Filter 2 VI Image Processing mi Morphology to filter out particles that do not interest you National Instruments Corporation 4 3 IMAQ Vision for LabVIEW User Manual Chapter 4 Performing Particle Analysis separating Touching Particles Use the IMAQ Separation VI Image Processing Morphology or apply an erosion or an open function with the IMAQ Morphology VI to separate touc
131. olor sensitivity setting A higher sensitivity setting distinguishes colors with very close hue values Three color sensitivity settings are available in IMAQ Vision low medium and high Use the default low setting if the colors in the template are very different from the colors in the background or other objects that you are not interested in Increase the color sensitivity settings as the color differences decrease Use the Color Sensitivity control of the IMAQ Setup Match Color Pattern VI to set the color sensitivity Refer to Chapter 14 Color Inspection of the IMAQ Vision Concepts Manual for more information about color sensitivity Search Strategy Use the search strategy to optimize the speed of the color pattern matching algorithm The search strategy controls the step size subsampling factor and percentage of color information used from the template Choose from these strategies e Conservative Uses a very small step size the least amount of subsampling and all the color information present in the template The conservative strategy is the most reliable method to look for a template in any image at potentially reduced speed Kp Note Use the conservative strategy if you have multiple targets located very close to each other in the image e Balanced Uses values in between the aggressive and conservative strategies e Aggressive Uses a large step size a lot of subsampling and all the color spectrum information from th
132. on Vision Builder AI follow the instructions in this tutorial e NI Vision Builder for Automated Inspection Configuration Help lIf you need descriptions or step by step guidance about how to use any of the NI Vision Builder AI functions to create an automated vision inspection system refer to this help file e NI Vision Builder for Automated Inspection Inspection Help lIt you need information about how to run an automated vision inspection system using NI Vision Builder AI refer to this help file IMAQ Vision for LabVIEW User Manual xii ni com About This Manual Other Documentation e Your National Instruments IMAQ device user manual If you need installation instructions and device specific information refer to your device user manual e Getting Started With IMAQ for Windows 2000 NT XP lIf you need instructions for installing the NI IMAQ software and your IMAQ hardware connecting your camera running Measurement amp Automation Explorer MAX and the NI IMAQ Diagnostics selecting a camera file and acquiring an image refer to this getting started document e NI IMAQ User Manual lIf you need information about how to use NI IMAQ and IMAQ image acquisition devices to capture images for processing refer to this manual e NI IMAQ VI or function reference guides If you need information about the features functions and operation of the NI IMAQ image acquisition VIs or functions refer to these help files e IMAQ
133. on for LabVIEW User Manual Calibrating Images This chapter describes how to calibrate your imaging system save calibration information and attach calibration information to an image After you set up your imaging system you may want to calibrate your system If your imaging setup is such that the camera axis 1s perpendicular or nearly perpendicular to the object under inspection and your lens has no distortion use simple calibration With simple calibration you do not need to learn a template Instead you define the distance between pixels in the horizontal and vertical directions using real world units If your camera axis is not perpendicular to the object under inspection use perspective calibration to calibrate your system If your lens is distorted use nonlinear distortion calibration Perspective and Nonlinear Distortion Calibration Perspective errors and lens aberrations cause images to appear distorted This distortion misplaces information in an image but it does not necessarily destroy the information in the image Calibrate your imaging system if you need to compensate for perspective errors or nonlinear lens distortion Complete the following general steps to calibrate your imaging system 1 Define a calibration template 2 Define a reference coordinate system 3 Learn the calibration information After you calibrate your imaging system you can attach the calibration information to an image Refer to th
134. ookup tables 2 14 setting up imaging system 2 1 morphology binary 4 2 grayscale 2 15 National Instruments support and services B 1 NI IMAQ xiii 2 2 A 1 A 2 Nth order filters 2 15 0 OCR 5 29 P particle analysis connectivity 4 3 creating binary image 4 1 improving binary image improving particle shapes 4 4 removing unwanted particles 4 3 separating touching particles 4 4 particle measurements 4 4 National Instruments Corporation l 7 Index particle measurements 4 4 pattern matching See also color pattern matching building coordinate reference 5 6 finding measurement points defining and creating template images 5 13 defining search area 5 15 general steps 5 13 learning the template 5 15 setting matching parameters and tolerances 5 17 testing search tool on test images 5 18 verifying results with ranking method 5 18 PDF417 barcodes reading 5 31 perspective errors calibrating See calibration pixel coordinates converting to real world coordinates 5 25 points finding See measurement points finding programming examples NI resources B 1 R ranking method for verifying pattern matching 5 18 reading 1D barcodes 5 30 AVI files 2 8 barcodes 5 30 characters 5 29 data matrix barcodes 5 30 PDF417 barcodes 5 31 reading images 2 6 regions of interest defining for calibration 6 6 interactively displaying tools palette in separate window 3 4 IMAQ Vision for L
135. ore that reflects how well the software learned the input image A learning score above 800 indicates that you chose the appropriate learning algorithm that the grid image complies with the guideline and that your vision system setup is adequate National Instruments Corporation 6 7 IMAQ Vision for LabVIEW User Manual Chapter 6 Calibrating Images If the learning process returns a learning score below 600 try the following 1 Make sure your grid complies with the guidelines listed in the Defining a Calibration Template section of this chapter 2 Check the lighting conditions If you have too much or too little lighting the software may estimate the center of the dots incorrectly Also adjust your Threshold Range to distinguish the dots from the background 3 Select another learning algorithm When nonlinear lens distortion is present using perspective projection sometimes results in a low learning score Kj Note A high score does not reflect the accuracy of your system Learning the Error Map An error map helps you gauge the quality of your complete system The error map returns an estimated error range to expect when a pixel coordinate is transformed into a real world coordinate The transformation accuracy may be higher than the value the error range indicates Set the Learn Error Map element of the Calibration Learn Setup control to learn the error map Learning the Correction Table If the speed of image correctio
136. ors with a lower intensity Define the neighborhood with a structuring element Refer to Chapter 9 Binary Morphology of the IMAQ Vision Concepts Manual for more information about structuring elements e Dilation Increases the brightness of pixels surrounded by neighbors with a higher intensity A dilation has the opposite effect of an erosion e Opening Removes bright pixels isolated in dark regions and smooths boundaries e Closing Removes dark spots isolated in bright regions and smooths boundaries e Proper opening Removes bright pixels isolated in dark regions and smooths the boundaries of regions e Proper closing Removes dark pixels isolated in bright regions and smooths the boundaries of regions e Auto median Generates simpler particles that have fewer details Use FFT to convert an image into its frequency domain In an image details and sharp edges are associated with mid to high spatial frequencies because they introduce significant gray level variations over short distances Gradually varying patterns are associated with low spatial frequencies An image can have extraneous noise such as periodic stripes introduced during the digitization process In the frequency domain the periodic pattern is reduced to a limited set of high spatial frequencies Also the imaging setup may produce non uniform lighting of the field of view which produces an image with a light drift superimposed on the information you wa
137. osing and opening operations that you can use to fill small holes and smooth the boundaries of objects A finite combination of successive opening and closing operations that you can use to remove small particles and smooth the boundaries of objects Obtaining various measurements of objects in an image A property of an event or system in which data is processed as it is acquired instead of being accumulated and processed at a later time The number of rows and columns of pixels An image composed of m rows and n columns has a resolution of m xX n Inverts the pixel values in an image producing a photometric negative of the image A color encoding scheme using red green and blue RGB color information where each pixel in the color image is encoded using 32 bits eight bits for red eight bits for green eight bits for blue and eight bits for the alpha value unused A color encoding scheme using red green and blue RGB color information where each pixel in the color image is encoded using 64 bits 16 bits for red 16 bits for green 16 bits for blue and 16 bits for the alpha value unused An edge detection algorithm that extracts the contours in gray level favoring diagonal edges IMAQ Vision for LabVIEW User Manual G 14 ni com ROI ROI tools rotational shift rotation invariant matching S sample saturation scale invariant matching segmentation function separation function shift invariant match
138. ou perform web inspection tasks include locating structural defects on wood planks or detecting cracks on plastic sheets Figure 4 1 illustrates the steps involved in performing particle analysis Create a Binary Image Improve a Binary Image Make Particle Measurements in Pixels or Real World Units Figure 4 1 Steps for Performing Particle Analysis Create a Binary Image Threshold your grayscale or color image to create a binary image Creating a binary image separates the objects that you want to inspect from the background The threshold operation sets the background pixels to 0 in the binary image while setting the object pixels to a non zero value Object pixels have a value of 1 by default but you can set the object pixels to have any value you choose You can use different techniques to threshold your image If all the objects of interest in your grayscale image fall within a continuous range of intensities and you can specify this threshold range manually use the IMAQ Threshold VI Image Processing Processing to threshold your image If all the objects in your grayscale image are either brighter or National Instruments Corporation 4 1 IMAQ Vision for LabVIEW User Manual Chapter 4 Performing Particle Analysis q a darker than your background you can use one of the automatic thresholding techniques in IMAQ Vision Complete the following steps to use one of the automatic thresholding techniques 1 Use the
139. perform By default the color pattern matching algorithm learns only those features from the template that are necessary for shift invariant matching However if you want to match the template at any orientation the learning process must consider the possibility of arbitrary orientations Use the IMAQ Setup Learn Color Pattern VI Machine Vision Searching and Matching to specify which type of learning mode to use Then use the IMAQ Learn Color Pattern VI Machine Vision Searching and Matching to learn the template Exclude colors in the template that you are not interested in using during the search phase Ignore colors that make your template difficult to locate When a template differs from several regions of the search image by only its primary color or colors consider ignoring the predominant common color to improve search performance Typically the predominant color is the background color of the template IMAQ Vision for LabVIEW User Manual 5 20 ni com Chapter 5 Performing Machine Vision Tasks Use the IMAQ Setup Learn Color Pattern VI to ignore colors You can ignore certain predefined colors by using Ignore Black and White To ue ie ignore other colors first learn the colors to ignore using IMAQ ColorLearn aa Then set the Ignore Color Spectra control of the IMAQ Setup Learn Color Pattern VI to the resulting color spectrum The learning process is time intensive because the algorithm attempts to find unique features of th
140. pixel A color or pattern that you are trying to match in an image using the color matching or pattern matching functions A template can be a region selected from an image or it can be an entire image Separates particles from the background by assigning all pixels with intensities within a specified range to the particle and the rest of the pixels to the background In the resulting binary image particles are represented with a pixel intensity of 255 and the background is set to 0 Two parameters the lower threshold gray level value and the upper threshold gray level value Tagged Image File Format An image format commonly used for encoding 8 bit 16 bit and color images TIFF images have the file extension TIF Describes algorithms that are designed to support a lower and upper bound on execution time A collection of tools that enable you to select regions of interest zoom in and out and change the image palette G 16 ni com Glossary value The grayscale intensity of a color pixel computed as the average of the maximum and minimum red green and blue values of that pixel VI Virtual Instrument 1 A combination of hardware and or software elements typically used with a PC that has the functionality of a classic stand alone instrument 2 A LabVIEW software module which consists of a front panel user interface and a block diagram program National Instruments Corporation G 17 IMAQ Vision for LabVIEW User Manu
141. r in the search region and that are concentric to the outer circular boundary Control the number of concentric search lines that are used for the edge detection by specifying the radial distance between the concentric lines in pixels Specify the direction of the search as either clockwise or counterclockwise IMAQ Vision for LabVIEW User Manual 5 12 ni com Chapter 5 Performing Machine Vision Tasks Finding Points Using Pattern Matching The pattern matching algorithms in IMAQ Vision measure the similarity between an idealized representation of a feature called a template and the feature that may be present in an image A feature is a specific pattern of pixels in an image Pattern matching returns the location of the center of the template and the template orientation Complete the following generalized steps to find features in an image using pattern matching 1 Define a reference or fiducial pattern to use as a template image 2 Use the reference pattern to train the pattern matching algorithm with B IMAQ Learn Pattern 2 3 Define an image or an area of an image as the search area A small search area can reduce the time to find the features y 4 Set the tolerances and parameters to specify how the algorithm B operates at run time using IMAQ Setup Match Pattern 2 Ps 5 Test the search algorithm on test images using IMAQ Match Pattern 2 B 6 Verify the results using a ranking method Defining and Creating Good Template I
142. rence to the source image s and to a destination image or the VIs may have an optional destination image If you do not provide a destination image the VI modifies the source image At the end of your application dispose of each image that you created using the IMAQ Dispose VI Vision Utilities Image Management National Instruments Corporation 2 3 IMAQ Vision for LabVIEW User Manual Chapter 2 Getting Measurement Ready Images Input and Output Combinations Depending on the type of function a VI performs different combinations of input and output are possible You can use this flexibility to decide which image to process and where to store the resulting image If no destination image is wired the source image is used and passed to the destination output The figures in the following sections show several VI connector panes used in IMAQ Vision Image Analysis The following connector pane applies only to VIs that analyze an image and therefore do not modify either the size or contents of the image Examples of these types of operations include particle analysis and histogram calculations Image Results Parameters Image Masks The following connector pane introduces an Image Mask Image Image Mask Parameters The presence of an Image Mask input indicates that the processing or analysis is dependent on the contents of another image the Image Mask The only pixels in Image that are processed are thos
143. represents IMAQ Vision for LabVIEW User Manual 3 14 ni com Chapter 3 Making Grayscale and Color Measurements 3 amp fuses much better and results in high match scores near 800 for both 3 amp fuses Use as many samples as you want in an image to learn the representative color spectrum for a specified template 1 Regions Used to Learn Color Information Figure 3 9 Using Multiple Regions to Learn Color Distribution Choosing a Color Representation Sensitivity When you learn a color you need to specify the sensitivity required to specify the color information An image containing a few well separated colors in the color space requires a lower sensitivity to describe the color than an image that contains colors that are close to one another in the color vi space Use the Color Sensitivity control of the IMAQ ColorLearn VI to a specify the granularity you want to use to represent the colors Refer to the Color Sensitivity section of Chapter 5 Performing Machine Vision Tasks for more information about color sensitivity National Instruments Corporation 3 15 IMAQ Vision for LabVIEW User Manual Chapter 3 Making Grayscale and Color Measurements Ignoring Learned Colors Ignore certain color components in color matching by replacing the corresponding component in the input color spectrum array to 1 For example by replacing the last component in the color spectrum with 1 the white color is ignored during the color matchi
144. res Use the Color Score Weight control to set the color score weight Minimum Contrast Use the minimum contrast to increase the speed of the color pattern matching algorithm The color pattern matching algorithm ignores all image regions where grayscale contrast values fall beneath a minimum contrast value Use the Minimum Contrast control to set the minimum contrast Refer to the Setting Matching Parameters and Tolerances section of this chapter for more information about minimum contrast Rotation Angle Ranges Refer to the Setting Matching Parameters and Tolerances section of this chapter for information about rotation angle ranges Testing the Search Algorithm on Test Images Refer to the previous Testing the Search Algorithm on Test Images section of this chapter for information about testing the search algorithm IMAQ Vision for LabVIEW User Manual 5 24 ni com Chapter 5 Performing Machine Vision Tasks Finding Points Using Color Location Color location algorithms provide a quick way to locate regions in an image with specific colors Use color location when your application has the following characteristics e Requires the location and the number of regions in an image with their specific color information e Relies on the cumulative color information in the region instead of the color arrangement in the region e Does not require the orientation of the region e Does not always require the location with subpixel accuracy
145. rlay Bitmap VI 5 32 IMAQ Overlay Line VI 5 32 IMAQ Overlay Multiple Lines VI 5 32 IMAQ Overlay Oval VI 5 32 IMAQ Overlay Points VI 5 32 IMAQ Overlay Rectangle VI 5 32 A 12 IMAQ Overlay ROI VI 5 32 IMAQ Overlay Text VI 5 32 IMAQ Particle Analysis Report VI 4 4 IMAQ Particle Analysis VI 4 4 IMAQ Particle Filter 2 VI 4 3 IMAQ Perpendicular Line VI 5 27 IMAQ Point Distance VI 5 26 IMAQ Polygon Area VI 5 27 IMAQ Quantify VI 3 9 IMAQ Rake VI 5 12 IMAQ Read Barcode VI 5 30 IMAQ Read Classifier File VI 5 28 IMAQ Read Data Matrix Barcode VI 5 30 IMAQ Read Image and Vision Info VI 2 7 5 33 IMAQ Read LCD VI 5 28 IMAQ Read Meter VI 5 27 IMAQ Read PDF417 Barcode VI 5 31 National Instruments Corporation l 5 Index IMAQ Read Single Digit VI 5 28 IMAQ ReadFile VI 2 7 IMAQ RejectBorder VI 4 3 IMAQ Remote Compression VI A 3 IMAQ RemoveParticle VI 4 3 IMAQ ReplaceColorPlanes VI 3 10 IMAQ RGBToColor2 VI 3 12 IMAQ ROIProfile VI 2 13 5 11 IMAQ ROIToMask VI 3 5 IMAQ RT Video Out VI A 4 IMAQ Select Line VI 3 6 IMAQ Select Point VI 3 6 IMAQ Select Rectangle VI 3 6 5 26 IMAQ Separation VI 4 4 IMAQ Sequence VI 2 7 IMAQ Setup Learn Color Pattern VI 5 20 IMAQ Setup Learn Pattern 2 VI 5 15 IMAQ Setup Match Color Pattern VI 5 22 IMAQ Setup Match Pattern 2 VI 5 17 IMAQ Simple Edge VI 5 11 IMAQ Snap VI 2 7 IMAQ Spoke VI 5 12 IMAQ Start Timed Execution VI A 8 A 9 IMAQ Stop Timed Ex
146. rmations for expanding dilating or reducing eroding objects filling holes closing inclusions or smoothing borders They are used primarily to delineate objects and prepare them for quantitative inspection analysis Uses an M shaped structuring element in the skeleton function IMAQ Vision for LabVIEW User Manual Glossary neighbor neighborhood operations NLIMAQ nonlinear filter nonlinear gradient filter nonlinear Prewitt filter nonlinear Sobel filter Nth order filter number of planes in an image OCR OCV IMAQ Vision for LabVIEW User Manual A pixel whose value affects the value of a nearby pixel when an image is processed The neighbors of a pixel are usually defined by a kernel or a structuring element Operations on a point in an image that take into consideration the values of the pixels neighboring that point The driver software for National Instruments IMAQ hardware Replaces each pixel value with a nonlinear function of its surrounding pixels A highpass edge extraction filter that favors vertical edges A highpass edge extraction filter based on 2D gradient information A highpass edge extraction filter based on 2D gradient information The filter has a smoothing effect that reduces noise enhancements caused by gradient operators Filters an image using a nonlinear filter This filter orders or classifies the pixel values surrounding the pixel being processed The pixel being pro
147. rowser Vision Utilities Vision Utilities functions allow you to manipulate and display images in IMAQ Vision aa e Image Management A group of VIs that manage images Use these VIs to create and dispose images set and read attributes of an image such as its size and offset and copy one image to another You also can use some of the advanced VIs to define the border region of an image and access the pointer to the image data e IMAQ Vision for LabVIEW User Manual Files A group of VIs that read images from files write images to files in different file formats and get information about the image contained in a file External Display A group of VIs that control the display of images in external image windows Use these VIs to complete the following tasks Get and set window attributes such as size position and zoom factor Assign color palettes to image windows Set up and use image browsers Setup and use different drawing tools to interactively select ROIs on image windows Detect draw events Retrieve information about ROIs drawn on the image window 1 2 ni com Chapter 1 Introduction to IMAQ Vision ig Note If you have LabVIEW 7 0 or later you also can use the Image Display control available from the Vision control palette r ap ae Region of Interest A group of VIs that manage ROIs Use these VIs to programmatically define ROIs and convert ROIs to and from image masks
148. s specific to the Image Display control appear at the end of the popup menu e Palette Determines which color palette the Image Display control uses to display images You can configure the control to use a predefined color palette or a custom color palette Define a custom color palette with the User Palette property node You also can change the color palette of the control or an image probe at run time by right clicking the Image Display control National Instruments Corporation 2 11 IMAQ Vision for LabVIEW User Manual Chapter 2 Getting Measurement Ready Images e Maximum Contour Count Sets the maximum number of ROI contours a user can draw on an image display The Image Display control also includes the following methods e Get Last Event Returns the last user event resulting from mouse movements and clicks on the Image Display control This method has the same behavior as IMAQ WindLastEvent does for external display windows e Clear ROI Removes any ROIs on the Image Display control e Refresh Image Refreshes the display to show the latest image This method is useful if the snapshot control is disabled but you want the Image Display control to show the latest changes to the image Attach Calibration Information If you want to attach the calibration information of the current setup to am each image you acquire use the IMAQ Set Calibration Info VI Vision o Utilities Calibration This VI takes in a source imag
149. s perform basic morphological operations such as dilation and erosion on grayscale and binary images Other VIs improve the quality of binary images by filling holes in particles removing particles that touch the image border removing small particles and removing unwanted particles based on different shape characteristics of the particle Another set of VIs in this subpalette separate touching particles find the skeleton of particles and detect circular particles Analysis A group of VIs that analyze the content of grayscale and binary images Use these VIs to compute the histogram information and grayscale statistics of an image retrieve pixel information and statistics along any one dimensional profile in an image and detect and measure particles in binary images Color Processing A group of VIs that analyze and process color images Use these VIs to compute the histogram of color images apply lookup tables to color images change the brightness contrast and gamma information associated with a color image and threshold a color image Some of these VIs also compare the color information in different images or different regions in an image using a color matching process Operators A group of VIs that perform basic arithmetic and logical operations on images Use some of these VIs to add subtract multiply and divide an image with other images or constants Use other VIs in this subpalette to apply logical operations such as
150. se it was acquired in an environment without sufficient light the majority of your pixels will have low intensity values which appear as a concentration of peaks on the left side of your histogram If your image is overexposed because it was acquired in an environment with too much light the majority of the pixels will have high intensity values which appear as a concentration of peaks on the right side of your histogram If your image has an appropriate amount of contrast your histogram will have distinct regions of pixel concentrations Use the histogram information to decide if the image quality is sufficient enough to separate objects of interest from the background If the image quality meets your needs use the histogram to determine the range of pixel values that correspond to objects in the image You can use this range in processing functions such as determining a threshold range during particle analysis If the image quality does not meet your needs try to improve the imaging conditions to get the necessary image quality You may need to re evaluate and modify each component of your imaging setup lighting equipment and setup lens tuning camera operation mode and acquisition device parameters If you reach the best possible conditions with your setup but the image quality still does not meet your needs try to improve the image quality using the image processing techniques described in the Jmprove an Image section of this chap
151. sion control palette has the following elements e IMAQ Image ctl This control is the type definition that describes the image data type You can use this control to represent the image data type on the front panel of a VI For example use this control as an input or output of a subVI so that a calling VI can pass an image to the subVI In LabVIEW 6 x this control is located on the IMAQ Vision control palette e Image Display tuUse this control to display your images directly on the LabVIEW front panel if you are using LabVIEW 7 0 or later You National Instruments Corporation 1 1 IMAQ Vision for LabVIEW User Manual Chapter 1 Introduction to IMAQ Vision w ia J h also can use this control to create regions of interest ROIs Classic and 3D versions are available IMAQ Vision controls Use these controls to get the functionality of corresponding IMAQ Vision VI controls directly into your own VIs Machine Vision controls Use these controls to get the functionality of corresponding Machine Vision VI controls directly into your own VIs IMAQ Vision Function Palettes IMAQ Vision for LabVIEW is organized into three main function palettes Vision Utilities Image Processing and Machine Vision This section describes these palettes and their subpalettes Kp Note This document references many VIs from the IMAQ Vision function palette If you have difficulty finding a VI use the search capability of the LabVIEW VI b
152. so can combine multiple edge locations to compute intersection points projections circles or ellipse fits Pattern matching algorithms use edges and patterns Pattern matching can locate with very high accuracy the position of fiducials or characteristic features of the part under inspection You can combine those locations to compute lengths angles and other object measurements The robustness of your measurement relies on the stability of your image acquisition conditions Sensor resolution lighting optics vibration control part fixture and general environment are key components of the imaging setup All elements of the image acquisition chain directly affect the accuracy of the measurements National Instruments Corporation 5 1 IMAQ Vision for LabVIEW User Manual Chapter 5 Performing Machine Vision Tasks Figure 5 1 illustrates the basic steps involved in performing machine vision Locate Objects to Inspect Set Search Areas Find Measurement Points Identify Parts Under Inspection Classify Read Read Objects Characters Barcodes Convert Pixel Coordinates to Real World Coordinates Display Results Figure 5 1 Steps for Performing Machine Vision Kp Note Diagram items enclosed with dashed lines are optional steps Locate Objects to Inspect In a typical machine vision application you extract measurements from ROIs rather than the entire image To use this technique the parts of the object you are interes
153. spect See machine vision IMAQ Vision for LabVIEW User Manual lookup table transformations 2 14 lowpass filters 2 15 lowpass frequency filters attenuation 2 17 truncation 2 17 machine vision converting pixel coordinates to real world coordinates 5 25 defining region of interest for search area interactively 5 8 programmatically 5 9 displaying results 5 31 finding measurement points color location 5 25 color pattern matching 5 18 edge detection 5 9 pattern matching 5 13 locating objects to inspect choosing method for building coordinate reference figure 5 7 edge detection for building coordinate reference 5 3 pattern matching for building coordinate reference 5 6 making measurements analytic geometry measurements 5 27 distance measurements 5 26 instrument reader measurements 5 27 overview 5 1 steps for performing figure 5 2 Machine Vision controls 1 2 Machine Vision function palettes 1 5 masks for defining regions of interest 3 9 measurement points finding color location 5 25 color pattern matching 5 18 ni com edge detection 5 9 pattern matching 5 13 measurement ready images acquiring acquiring or reading images 2 6 analyzing images 2 12 attaching calibration information 2 12 calibrating imaging system 2 2 creating images 2 2 displaying images 2 8 improving images advanced operations 2 18 FFT Fast Fourier Transform 2 16 filters 2 14 grayscale morphology 2 15 l
154. splay during development and debugging to view your images from your host machine just as you would view the LabVIEW front panels of the VIs running on your LabVIEW RT system Use RT Video Out to display your images on a monitor connected to your remote LabVIEW RT system IMAQ Vision for LabVIEW User Manual A 2 ni com Appendix A Vision for LabVIEW Real Time Remote Display Remote Display allows you to acquire images on your remote system and view them on your host machine Remote Display is automatically enabled when you use the LabVIEW Image Display control available with LabVIEW 7 0 or later or any of the IMAQ Vision display VIs Vision 4 Utilities External Display such as IMAQ WindDraw IMAQ fe WindToolsShow and IMAQ ConstructROI Remote Display is useful for monitoring and debugging your Vision for LabVIEW RT applications Familiarize yourself with how Remote Display works before using this feature The following details will help you prepare your application for use with Remote Display e Remote Display is a front panel feature Therefore your Lab VIEW front panel must be open for you to see images displayed using Remote Display e Remote Display performs best when combined with IMAQ Remote E Compression Vision Utilities IMAQ RT When you display images on your remote machine LabVIEW must send those images over your network This process can take up a large amount of your network bandwidth especially when tr
155. square reduces the reliability of your application By default IMAQ Read Data Matrix Barcode automatically detects the type of barcode to read You can improve the performance of the VI by specifying the type of barcode in your application IMAQ Vision supports Data Matrix types ECC 000 to ECC 140 and ECC 200 Reading PDF417 Barcodes ET Use IMAQ Read PDF417 Barcode Machine Vision Instrument E Readers to read values encoded in a PDF417 barcode IMAQ Read PDF417 Barcode can automatically locate one or multiple PDF417 barcodes in an image However you can improve the inspection performance by locating the barcodes using one of the techniques described in Chapter 5 Performing Machine Vision Tasks and then passing in ROI Descriptors of the locations into IMAQ Read PDF417 Barcode W Tip Ifyou need to read only one barcode per image set Search Mode to Single Barcode Conservative to increase the speed of the VI Display Results You can overlay the results obtained at various stages of your inspection process on the inspection image IMAQ Vision attaches the information that you want to overlay to the image but it does not modify the image The overlay appears every time you display the image National Instruments Corporation 5 31 IMAQ Vision for LabVIEW User Manual Chapter 5 i IMAQ Vision for LabVIEW User Manual Performing Machine Vision Tasks E o E ye ag eH on a E A o Use the followin
156. tains a compact description of the color information that you learned Refer to Chapter 14 Color Inspection of the IMAQ Vision Concepts Manual for more information Use the color spectrum to represent the learned color information for all subsequent matching operations 3 Define an image or multiple regions in an image as the inspection or comparison area 4 Use the IMAQ ColorMatch VI Image Processing Color Processing to compare the learned color information to the color information in the inspection regions This VI returns a score that indicates the closeness of match You can specify a Minimum Match Score which indicates if there is a match between the input color information and the color in each specified region in the image 5 Use the color matching score as a measure of similarity between the reference color information and the color information in the image regions being compared Learning Color Information When learning color information choose the color information carefully by specifying an image or regions in an image that contain the color or color set that you want to learn selecting how detailed you want the color information to be learned and choosing colors that you want to ignore during matching IMAQ Vision for LabVIEW User Manual 3 12 ni com Chapter 3 Making Grayscale and Color Measurements Specifying the Color Information to Learn Because color matching uses only color information to measure similarit
157. ted in must always appear inside the ROIs you define If the object under inspection is always at the same location and orientation in the images you need to process defining ROIs is straightforward Refer to the Set Search Areas section of this chapter for information about selecting an ROI Often the object under inspection appears shifted or rotated in the image you need to process relative to the reference image in which you located the object When this occurs the ROIs need to shift and rotate with the parts of the object in which you are interested For the ROIs to move with the object you need to define a reference coordinate system relative to the object in the reference image During the measurement process the coordinate system moves with the object when the object appears shifted IMAQ Vision for LabVIEW User Manual 5 2 ni com Chapter 5 Performing Machine Vision Tasks and rotated in the image you need to process This coordinate system is referred to as the measurement coordinate system The measurement VIs automatically move the ROIs to the correct position using the position of the measurement coordinate system relative to the reference coordinate system Refer to Chapter 13 Dimensional Measurements of the IMAQ Vision Concepts Manual for information about coordinate systems You can build a coordinate transformation using edge detection or pattern matching The output of the edge detection and pattern matching VIs that bu
158. ted to Image Dst the processed image is placed into the original image and the original image data is lost The Image Dst input is the image that receives the processing results Depending on the functionality of the VI this image can be either the same or a different image type as that of the source image The VI descriptions in the IMAQ Vision for LabVIEW Help include the type of image that can be connected to the Image inputs The image connected to Image Dst is resized to the source image size National Instruments Corporation 2 5 IMAQ Vision for LabVIEW User Manual Chapter 2 Getting Measurement Ready Images Arithmetic and Logical Operations The following connector pane applies to VIs that perform arithmetic or logical operations between two images Image Sro Image Dst Image Sre B Parameters Image Dst Cut Two source images exist for the destination image You can perform an operation between two images A and B and then either store the result in another image Image Dst or in one of the two source images A or B In the latter case you can consider the original data to be unnecessary after the processing has occurred The following combinations are possible in this pane In the pane on the left the three images are all different Image Sre A and Image Src B are intact after processing and the results from this operation are stored in Image Dst In the center pane Image Src A also is connected to the
159. tensity 3 9 percent of image analyzed 3 9 standard deviation 3 9 grayscale morphology 2 15 H help technical support B 1 highpass filters 2 15 highpass frequency filters attenuation 2 17 truncation 2 17 National Instruments Corporation Index ignoring learned colors 3 16 image analysis connector pane example 2 4 Image Display control 2 9 image mask connector pane example 2 4 Image Processing function palettes 1 4 images See also particle analysis acquiring or reading 2 6 figure 1 7 analyzing 2 12 attaching calibration information 2 12 6 10 creating connector panes 2 4 Image Dst input 2 5 Image Mask input 2 4 multiple images 2 3 overview 2 2 source images for destination image 2 5 valid image types 2 2 degradation A 3 displaying 1 1 2 8 improving advanced operations 2 18 FFT Fast Fourier Transform 2 16 filters 2 14 grayscale morphology 2 15 lookup tables 2 14 imaging system calibrating 2 2 setting up 2 1 IMAQ ArrayToComplexImage VI 2 18 IMAQ ArrayTolImage VI 2 8 IMAQ AutoBThreshold VI 4 2 IMAQ AVI Close VI 2 8 IMAQ AVI Open VI 2 8 IMAQ AVI Read Frame VI 2 8 IMAQ Bisecting Line VI 5 27 IMAQ Vision for LabVIEW User Manual Index IMAQ Browser Delete VI A 11 IMAQ Browser Focus Setup VI A 11 IMAQ Browser Focus VI A 11 IMAQ Browser Insert VI A 11 IMAQ Browser Replace VI A 11 IMAQ Browser Setup VI A 11 IMAQ Centroid VI 3 10 IMAQ Check Timed Execut
160. ter fie Use the IMAQ LineProfile VI Image Processing Analysis to get the pixel distribution along a line in the image or use the IMAQ ROIProfile VI F Image Processing Analysis to get the pixel distribution along a one dimensional path in the image To use a line profile to analyze your image draw or specify a line across the boundary of an object in your image Use IMAQ LineProfile to examine the pixel values along the line By looking at the pixel distribution along this line you can determine if the image quality is good enough to provide you with sharp edges at object boundaries Also you can determine if the image is noisy and identify the characteristics of the noise If the image quality meets your needs use the pixel distribution information to determine some parameters of the inspection functions you want to use For example use the information from the line profile to determine the strength of the edge at the boundary of an object You can National Instruments Corporation 2 13 IMAQ Vision for LabVIEW User Manual Chapter 2 Getting Measurement Ready Images H input this information into the IMAQ Edge Tool VI Machine Vision Caliper to find the edges of objects along the line Improve an Image Lookup Tables q d F q Filters Using the information you gathered from analyzing your image you may want to improve the quality of your image for inspection You can improve your image
161. tern Matching to Build a Coordinate Transformation 5 6 Choosing a Method to Build the Coordinate Transformation 065 5 6 Eb SAPO MATAS frer a dene as wee owitvessdaursatnenscegae E 5 8 Detinine Recions TnteracHvel yssen Uaghssesek T 5 8 Defining Regions Programmatically cccccssssssssessseesseeeesseesseeseeeeseeeeeeeees 5 9 Find Measure ment POME asanarea eno E AN 5 9 Finding Features Using Edge Detection cccccceeeeseeeeeeesseeeeseeeeseeeeeeeeees 5 9 Pind ines 01 CAP CleS nastier a ERN 5 9 Finding Edge Points Along One Search Contour c c sccseeeee 5 11 Finding Edge Points Along Multiple Search Contours 5 12 Finding Points Using Pattern Matching cccccsseseeeeeseeeeeseeeeeeeeeseeeeseeees 5 13 Defining and Creating Good Template Images cccccceeeeeeeee 5 13 Training the Pattern Matching Algorithm cccccccceccsssseeeeeseees 5 15 Perminas a SC AEC IAT Triono hoine i an 5 15 Setting Matching Parameters and Tolerances cccccccccccceeeeeeeees 5 17 Testing the Search Algorithm on Test Images cccccsssssseeeeeeees 5 18 Using a Ranking Method to Verify Results cccccccccececeeeeeeeseees 5 18 Finding Points Using Color Pattern Matching cccccceeeeeeeseeeeeeeeeeeeeees 5 18 Defining and Creating Good Color Template Images 5 19 Training the Color Pattern
162. the calibration information you can save it so that you do not have to relearn the information for subsequent processing Use the IMAQ Write Image and Vision Info VI Vision Utilities Calibration to save the image of the grid and its associated calibration information to a file To read the file containing the calibration information use the IMAQ Read Image and Vision Info VI Vision Utilities Calibration Refer to the Attach Calibration Information section of this chapter for more information about attaching the calibration information you read from another image Attach Calibration Information ja Ji Note Now that you have calibrated your setup correctly you can apply the calibration settings to images that you acquire Use the IMAQ Set Calibration Info VI Vision Utilities Calibration to attach the calibration information of the current setup to each image you acquire This VI takes in a source image containing the calibration information and a destination image that you want to calibrate The destination image is your inspection image with the calibration information attached to it The source image and destination image must be the same size IMAQ Vision for LabVIEW User Manual 6 10 ni com Chapter 6 Calibrating Images Using the calibration information attached to the image you can accurately ow convert pixel coordinates to real world coordinates to make any of the a analytic geometry measurements with IMAQ Convert Pi
163. tical directions Use simple calibration to map pixel coordinates to real world coordinates directly without a calibration grid The software rotates and scales a pixel coordinate according to predefined coordinate reference and scaling m factors You can assign the calibration to an arbitrary image using the 5 IMAQ Set Simple Calibration VI Vision Utilities Calibration To perform a simple calibration set a coordinate reference composed of an angle center and axis direction and scaling factors on the defined axis as shown in Figure 6 7 Express the angle between the x axis and the horizontal axis of the image in degrees Express the center as the position in pixels where you want the coordinate reference origin Set the axis direction to direct or indirect Simple calibration also offers a correction table option and a scaling mode option Simple calibration is performed using IMAQ Set Simple Calibration Use the Calibration Axis Info control to define the coordinate system Use the X Step and Y Step elements of the Grid Descriptor control to specify the scaling factors Use the Corrected Image Scaling control to set the scaling method Set the Learn Correction Table control to True to learn the correction table National Instruments Corporation 6 9 IMAQ Vision for LabVIEW User Manual Chapter 6 Calibrating Images 1 Origin Figure 6 7 Defining a Simple Calibration Save Calibration Information After you learn
164. ts Figure 1 2 Inspection Steps for Building a Vision Application Kp Note Diagram items enclosed with dashed lines are optional steps IMAQ Vision for LabVIEW User Manual 1 8 ni com Getting Measurement Ready Images This chapter describes how to set up your imaging system acquire and display an image analyze the image and prepare the image for additional processing set Up Your Imaging System Before you acquire analyze and process images you must set up your imaging system The manner in which you set up your system depends on your imaging environment and the type of analysis and processing you need to do Your imaging system should produce images with high enough quality so that you can extract the information you need from the images Complete the following steps to set up your imaging system 1 Determine the type of equipment you need given space constraints and the size of the object you need to inspect Refer to Chapter 3 System Setup and Calibration of the IMAQ Vision Concepts Manual for more information a Make sure your camera sensor is large enough to satisfy your minimum resolution requirement b Make sure your lens has a depth of field high enough to keep all of your objects in focus regardless of their distance from the lens Also make sure your lens has a focal length that meets your needs c Make sure your lighting provides enough contrast between the object under inspection and the backgrou
165. ultiple Data Matrix barcodes in an image However you can improve the inspection performance by locating the barcodes using one of the techniques described in Chapter 5 Performing Machine Vision Tasks and then passing in ROI Descriptors of the locations into IMAQ Read Data Matrix Barcode W Tip Ifyou need to read only one barcode per image set Search Mode to Single Barcode Conservative to increase the speed of the VI By default IMAQ Read Data Matrix Barcode detects if the barcode has black cells on a white background or white cells on a black background If the barcodes in your application have a consistent cell to background contrast you can improve the performance of the VI by setting Contrast to Black on White or White on Black By default IMAQ Read Data Matrix Barcode assumes the barcode cells are square If the barcodes you need to read have round cells set Cell Shape to Round Cells IMAQ Vision for LabVIEW User Manual 5 30 ni com Chapter 5 Performing Machine Vision Tasks ng Note Specify round cells only if the Data Matrix cells are round and have clearly defined edges If the cells in the matrix touch one another you must set Cell Shape to Square Cells By default IMAQ Read Data Matrix Barcode assumes the shape of the barcode is square If the shape of your barcode is rectangular set Barcode Shape to Rectangular Barcodes Kp Note Setting Barcode Shape to Rectangular Barcodes when the barcode you need to read is
166. under inspection Nonlinear distortion may occur from aberrations in the camera lens Perspective errors and lens aberrations cause images to appear distorted This distortion displaces information in an image but it does not necessarily destroy the information in the image Use simple calibration if you only want to assign real world coordinates to pixel coordinates Use perspective and nonlinear distortion calibration if you need to compensate for perspective errors and nonlinear lens distortion Refer to Chapter 6 Calibrating Images for detailed information about calibration Create an Image IMAG Use the IMAQ Create VI Vision Utilities Image Management to create an image reference When you create an image specify one of the following image data types e Grayscale U8 default 8 bit unsigned e Grayscale 116 16 bit signed e Grayscale SGL Floating point e Complex CSG e RGB U32 32 bit RGB IMAQ Vision for LabVIEW User Manual 2 2 ni com Chapter 2 Getting Measurement Ready Images e HSL U32 32 bit HSL e RGB U64 64 bit RGB You can create multiple images by executing IMAQ Create as many times as you want but each image you create requires a unique name Determine the number of required images through an analysis of your intended application Base your decision on different processing phases and whether you need to keep the original image after each processing phase ny Note If you plan to use filt
167. ure 6 5b shows an image of a calibration grid with perspective projection Figure 6 5c shows an image of a calibration grid with nonlinear distortion Figure 6 5 Types of Image Distortion IMAQ Vision for LabVIEW User Manual 6 6 ni com Chapter 6 Calibrating Images Choose the perspective projection algorithm when your system exhibits perspective errors only A perspective projection calibration has an accurate transformation even in areas not covered by the calibration grid as shown in Figure 6 6 Set the Distortion element of the Calibration Learn Setup control to Perspective to choose the perspective calibration algorithm Learning and applying perspective projection is less computationally intensive than the nonlinear method However perspective projection is not designed to handle highly nonlinear distortions If your imaging setup exhibits nonlinear distortion use the nonlinear method The nonlinear method guarantees accurate results only in the area that the calibration grid covers as shown in Figure 6 6 If your system exhibits both perspective and nonlinear distortion use the nonlinear method to correct for both Set the Distortion element of the Calibration Learn Setup control to Nonlinear to choose the nonlinear calibration algorithm 1 Calibration ROI Using the 2 Calibration ROI Using the Perspective Algorithm Nonlinear Algorithm Figure 6 6 Calibration ROIs Using the Learning Score The learning process returns a sc
168. ve a front panel Refer to the LabVIEW Real Time Module User Manual for recommended program architecture W Tip Refer to the Remote Display Errors section of this appendix for more information RT Video Out RT Video Out allows you to display images on a monitor that is connected to your RT target In IMAQ Vision IMAQ WindDraw and IMAQ g WindClose Vision Utilities External Display provide support for RT Video Out To display images on a monitor connected to your RT target input 15 for the Window Number control im Alternately you can use IMAQ RT Video Out Vision Utilities IMAQ RT to display image on a monitor connected to your RT target Kp Note This feature is available only on controllers that feature the 1815 chipset such as National Instruments PXI 8175 76 Series controllers and NI CVS 1450 Series devices RT Video Out supports overlay functionality However the overlay text is limited to one size and one font This display option is not a time bounded operation Refer to the Determinism in Vision for LabVIEW Real Time section of this appendix for more information about time bounded operations To programmatically configure your system to use RT Video Out for mitt displaying system images use the IMAQ Video Out Display Mode VI Vision Utilities IMAQ RT This VI allows you to set parameters for screen area color depth and refresh frequency Determinism in Vision for LabVIEW Real Time An algorithm exhibits det
169. xel to Real World Vision Utilities Calibration If your application requires that you make shape measurements you can use the calibrated measurements from the IMAQ Particle Analysis or IMAQ Particle Analysis Report VIs Image Processing Analysis You also can correct the image by removing o distortion with IMAQ Correct Calibrated Image Kp Note Correcting images is a time intensive operation A calibrated image is not the same as a corrected image Because calibration information is part of the image it is propagated throughout the processing and analysis of the image Functions that modify the image size such as an image rotation function void the calibration information Be Use IMAQ Write Image and Vision Info Vision Utilities Calibration to save the image and all of the attached calibration information to a file National Instruments Corporation 6 11 IMAQ Vision for LabVIEW User Manual Vision for LabVIEW Real Time This appendix introduces the real time capabilities of IMAQ Vision for LabVIEW and describes how you can use IMAQ Vision with LabVIEW RT to create a machine vision application for a real time deterministic embedded target About Vision for LabVIEW Real Time With LabVIEW RT NI IMAQ and IMAQ Vision for LabVIEW you have all the tools necessary to develop a complete machine vision application on a reliable embedded platform LabVIEW RT provides real time programming and execution capabilities NI
170. y the image or regions in the image representing the object should contain only the significant colors that represent the object as shown in Figure 3 6a Figure 3 6b illustrates an unacceptable region containing background colors Figure 3 6 Template Color Information The following sections explain when to learn the color information associated with an entire image a region in an image or multiple regions in an image Using the Entire Image You can use an entire image to learn the color spectrum that represents the entire color distribution of the image In a fabric identification application for example an entire image can specify the color information associated with a certain fabric type as shown in Figure 3 7 a T J E a Ye an La LP T A d k a Pa ini sd Figure 3 7 Using the Entire Image to Learn Color Distribution National Instruments Corporation 3 13 IMAQ Vision for LabVIEW User Manual Chapter 3 Making Grayscale and Color Measurements Using a Region in the Image You can select a region in the image to provide the color information for comparison A region is helpful for pulling out the useful color information in an image Figure 3 8 shows an example of using a region that contains the color information that is important for the application Figure 3 8 Using a Single Region to Learn Color Distribution Using Multiple Regions in the Image The interaction of light
171. y information Refer to Chapter 5 Performing Machine Vision Tasks for information about pattern matching templates and overlays National Instruments Corporation 2 IMAQ Vision for LabVIEW User Manual Chapter 2 Getting Measurement Ready Images 7 You also can use the IMAQ GetFileInfo VI Vision Utilities Files to retrieve image properties image size pixel depth recommended image type and calibration units without actually reading all the image data Use IMAQ AVI Open and IMAQ AVI Read Frame to open and read data from an AVI file stored on your computer into the image reference IMAQ Vision automatically converts the pixels it reads into the type of image you pass in Sg Ji Note When you are finished with the AVI file you must use IMAQ AVI Close to release resources associated with the AVI file E Use the IMAQ ArrayToImage VI Vision Utilities Pixel Manipulation to convert a 2D array to an image You also can use the Bec IMAQ ImageToArray VI Vision Utilities Pixel Manipulation to convert an image to a LabVIEW 2D array Display an Image You can display images in LabVIEW using two methods If you use LabVIEW 6 x you can display an image in an external window using the external display VIs on the External Display function palette If you use LabVIEW 7 0 or later you can use the above method or display an image directly on the front panel using the Image Display control on the Vision control palette External

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