Home

National Instruments IMAQ Vision for LabWindows TM /CVI User's Manual

1. Function Type Description Image Functions that create space in memory for images and perform basic image Management manipulation Memory Function that returns to the operating system previously used memory that is Management no longer needed Error Functions that set the current error return the name of the function in which the Management last error occurred return the error code of the last error and clear any pending errors Acquisition Functions that acquire images through an IMAQ hardware device Display Functions that cover all aspects of image visualization and image window management Overlay Functions that create and manipulate overlays Regions of Functions that create and manipulate regions of interest Interest File I O Functions that read and write images from and to files Calibration Functions that learn calibration information and correct distorted images Image Functions that compute the centroid of an image profile of a line of pixels Analysis and the mean line profile This type also includes functions that calculate the pixel distribution and statistical parameters of an image Grayscale Functions for grayscale image processing and analysis Processing Binary Functions for binary image processing and analysis Processing Color Functions for color image processing and analysis Processing Pattern Functions that learn patterns and search for patterns in images Matching IMAQ Vi
2. IMAQ IMAGE 116 16 bits per pixel signed monochrome IMAQ_ IMAGE _SGL 32 bits per pixel floating point monochrome ie p lt IMAQ_IMAGE_COMPLI 2 x 32 bits per pixel floating point native format after a Fast Fourier Transform FFT IMAQ_IMAGE_RGB 32 bits per pixel standard color IMAQ IMAGE HSL 32 bits per pixel color IMAQ IMAGE RGB _U64 64 bits per pixel standard color You can create multiple images by executing imaqCreateImage as many times as you want Determine the number of required images through an analysis of your intended application The decision is based on different processing phases and your need to keep the original image after each processing step The decision to keep an image occurs before each processing step 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 functions automatically allocate the appropriate amount of memory when the image size is modified For example functions that acquire or resample an image alter the image size so they allocate the appropriate memory space for the image pixels The return value of imagCreateImage is a pointer to the image structure Supply this pointer as an input to all subsequent IMAQ Vision functions Most functions in the IMAQ Vision li
3. 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 GridDescriptor structure 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 other calibration options selected this is an effective way to increase correction speeds Set the user defined ROI using the roi parameter of either imaqhearnCalibrationGrid or imaqhearnCalibrationPoints nye Note The user defined ROI represents the area in which you are interested The learning ROI is different from 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 Figure 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 EKER O P E S EE EE EE E E E ececoooo 0o 6 eooceoe cee eeee o e2ee0e00 eaoe
4. 6 8 characters reading 5 29 choosing learning algorithms 6 6 classifying samples 5 28 closing particles 4 4 tools palette 3 6 color defining color template images 5 20 pattern matching minimum contrast 5 24 setting sensitivity 5 23 using pattern matching to find points 5 19 color distribution learning in images 3 10 learning with a single ROI 3 10 learning with multiple ROIs 3 11 color images analyzing components 3 7 extracting planes 3 8 ignoring learned colors 3 13 processing 3 7 IMAQ Vision for LabWindows CVI User Manual Index color information learning 3 9 specifying 3 9 color location using to find points 5 25 color representation sensitivity specifying 3 12 color score weight 5 24 comparing color content in images 3 9 computing energy center of an image 3 7 energy center of an ROI in an image 3 7 configuring tools palette 3 6 conventions used in the manual ix converting 2D arrays to images 2 5 2 7 images to frequency domains 2 12 pixel coordinates to real world coordinates 5 26 planes of complex images to arrays 2 13 convolution filter 2 11 coordinate systems defining using edge detection 5 4 defining using pattern matching 5 6 correction tables learning 6 8 counting particles 4 4 creating binary images 4 1 images 2 2 Vision applications 1 4 D data matrix barcodes reading 5 30 defining calibration templates 6 2 color template images 5 20 coordinate s
5. IMAQ Vision for LabWindows CVI 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 closing 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 x 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 8 bits for red 8 bits for green 8 bits for blue and 8 bits for the alpha value unused A color encoding scheme using red green and blue RGB c
6. Proper closing Removes dark pixels isolated in bright regions and smooths the inner contours of particles e Auto median Generates simpler particles that have fewer details Use the Fast Fourier Transform 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 want to analyze In the frequency domain the light drift appears as a limited set of low frequencies around the average intensity of the image the DC component 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 imagFFT to convert an image from the spatial domain to the frequency domain This function computes the FFT of the image and results in a complex image representing the frequen
7. 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 two dimensional gradient information A highpass edge extraction filter based on two dimensional 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 processed 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 while an RGB image is composed of three planes one for the red component one for the blue and one for the green 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
8. See ROIs related documentation x removing unwanted particles 4 3 results displaying 5 31 ROIs defining 3 1 6 6 defining interactively 3 1 5 8 defining programmatically 3 6 5 9 rotating 5 2 shifting 5 2 rotating ROIs 5 2 S samples classifying 5 28 saving calibration information 6 10 scaling factors specifying 6 6 scaling methods setting 6 8 IMAQ Vision for LabWindows CVI User Manual Index search algorithm testing 5 18 5 25 search areas 5 10 defining 5 16 5 22 ROIs defining search areas 5 8 search strategies selecting for pattern matching 5 23 selecting pattern matching search strategies 5 23 separating touching particles 4 3 setting color sensitivity 5 23 pattern matching tolerances 5 23 scaling methods 6 8 setting up imaging systems 2 1 shifting ROIs 5 2 single ROI learning color distribution 3 10 smoothing boundaries of particles 4 3 software NI resources A 1 source images 2 4 specifying color information to learn 3 9 color representation sensitivity 3 12 scaling factors 6 6 support technical A 1 T taking color measurements 3 1 grayscale measurements 3 1 technical support A 1 template images background information 5 15 5 21 color information 5 20 defining color template images 5 20 feature detail 5 14 5 20 positional information 5 15 symmetry 5 14 5 20 IMAQ Vision for LabWindows CVI User Manual l 6 templates defining template image
9. 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 a window hold down the lt Ctrl gt key while drawing additional ROIs National Instruments Corporation 3 3 IMAQ Vision for LabWindows CVI User Manual Chapter 3 Making Grayscale and Color Measurements You can display the IMAQ Vision tools palette as part of an ROI constructor window or in a separate floating window Follow these steps to invoke an ROI constructor and define an ROI from within the ROI constructor window 1 Use imagConstructROI2 to display an image and the tools palette in an ROI constructor window as shown in Figure 3 2 ROI Constructor sik 70 Q oje gt C200 13 Bt Image x 45 Y 151 365 204 41 116 Draw an ROI on your image Resize and reposition the ROI until it designates the area you want to inspect Figure 3 2 ROI Constructor 2 Select an ROI tool from the tools palette 4 Click OK to output a descriptor of the region you selected You can input this ROI descriptor into many analysis and processing functions You can also convert the ROI descriptor into an image mask which you can use to process selected regions in the image Use imagROIToMask to convert the ROI descriptor into an image mask You can also use imagSelectPoint imaqSelectLine imaqSelectRect and imagSelectAnnulus to define regions of interest Complete th
10. EE EE DE EE E E EE E EE E 1 Center to Center Distance 2 Center of Grid Dots 3 Distance Between Dot Edges Figure 6 1 Defining a Calibration Grid 3 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 IMAQ Vision for LabWindows CVI User Manual 6 2 ni com Chapter 6 Calibrating Images Defining a Reference Coordinate System To express measurements in real world units you need to define a coordinate system in the image of the grid Use the CoordinateSystem structure to define a coordinate system by its origin angle and axis 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 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
11. Find Measurement Points After you set regions of inspection 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 Using Edge Detection Use the edge detection tools to identify and locate sharp discontinuities in an image Discontinuities typically represent abrupt changes in pixel intensity values which characterize the boundaries of objects National Instruments Corporation 5 9 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks Finding Lines or Circles If you want to find points along the edge of an object and find a line describing the edge use imaqFindEdge and imagFindConcentricEdges The imaqFindEdge function finds edges based on rectangular search areas as shown in Figure 5 5 The imagFindConcentricEdge function finds edges based on annular search areas 1 Search Region 3 Detected Edge Points 2 Search Lines 4 Line Fit to Edge Points Figure 5 5 Finding a Straight Feature IMAQ Vision for LabWindows CVI User Manual 5 10 ni com Chapter 5 Performing Machine Vision Tasks 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 imagFindCircularEdge 1 Annular Search Region 3 Detected Edge Points 2 Search Line
12. Vision for LabWindows CVI a part of the Vision Development Module is a library of C functions that you can use to develop machine vision and scientific imaging applications The Vision Development Module also includes the same imaging functions for LabVIEW and ActiveX controls for Microsoft 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 for Automated Inspection configurable machine vision software that you can use to prototype benchmark and deploy applications Application Development Environments This release of IMAQ Vision for LabWindows CVI supports the following Application Development Environments ADEs for Windows 2000 NT XP LabWindows CVI version 6 0 and later e Microsoft Visual C C version 6 0 and later ay Note IMAQ Vision has been tested and found to work with these ADEs although other ADEs may also work National Instruments Corporation 1 1 IMAQ Vision for LabWindows CVI User Manual Chapter 1 Introduction to IMAQ Vision IMAQ Vision Function Tree The IMAQ Vision function tree NIVision 1f p contains separate classes corresponding to groups or types of functions Table 1 1 lists the IMAQ Vision function types and gives a description of each type Table 1 1 IMAQ Vision Function Types
13. 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 the width and height and in the case of a rotated rectangle the rotation angle 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 mask image determine whether the corresponding pixel in the source image needs to be processed If a pixel in the image mask has a value different than 0 the corresponding pixel in the source image is processed If a pixel in the image mask has a value of 0 the corresponding pixel in the source image is left unchanged When you need to make intensity measurements on particles in an image you can use a mask to define the particles First threshold your image to make a new binary image For more information about binary images refer to Chapter 4 Performing Particle Analysis You can input the binary image IMAQ Vision for LabWindows CVI User Manual 3 6 ni com Chapter 3 Making Grayscale and Color Measurements or a labeled version of the binary image as a mask image to the intensity measurement function If you want to make color comparisons convert the binary image into an ROI descriptor using imaqMaskToROI Measure Grayscale Statistics You can measure grayscale statistics in images using light meters or quanti
14. colors may not be desirable during 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 learns the important features of the template Use imaqLearnColorPattern to learn the template The learning process depends on the type of matching that you expect to 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 learnMode element of the imaqlhearnColorPattern options parameter to specify which type of learning mode to use Exclude colors in the template that you are not interested in using during the search phase Typically you should ignore colors that either belong to the background of the object or are not unique to the template to reduce the potential for incorrect matches during the color location phase You can ignore certain predefined colors using the ignoreMode element
15. files e IMAQ 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 Example programs If you want examples of how to create specific applications go to lt CVI gt samples vision e 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 e 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 online magazine a product advisor and a community area where you can share ideas questions and source code with vision developers around the world National Instruments Corporation xi IMAQ Vision for LabWindows CVI User Manual Introduction to IMAQ Vision This chapter describes the IMAQ Vision for LabWindows CVI software outlines the IMAQ Vision function organization and lists the steps for making a machine vision application 3 Note Refer to the Vision Development Module Release Notes that came with your software for information about the system requirements and installation procedure for IMAQ Vision for LabWindows CVI About IMAQ Vision IMAQ
16. following 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 National Instruments Corporation 6 1 IMAQ Vision for LabWindows CVI User Manual Chapter 6 Calibrating Images Refer to Chapter 5 Performing Machine Vision Tasks 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 the grid method 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 desired working area e The radius of the dots in the acquired image should be 6 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 6 pixels as shown in Figure 6 1 dx i 0 0 y 0e 000o E EE EE EE EE E
17. 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 LabWindows CVI 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 10
18. groups or types of functions Table 1 2 lists the IMAQ Machine Vision function types and gives a description of each type Table 1 2 IMAQ Machine Vision Function Types Function Type Description Coordinate Transform Functions that find coordinate transforms based on image contents Count and Measure Objects Function that counts and measures objects in an image Find Patterns Function that finds patterns in an image Locate Edges Functions that locate different types of edges in an image National Instruments Corporation 1 3 IMAQ Vision for LabWindows CVI User Manual Chapter 1 Introduction to IMAQ Vision Table 1 2 IMAQ Machine Vision Function Types Continued Function Type Description Measure Distances Functions that measure distances between objects in an image Measure Intensities Functions that measure light intensities in various shaped regions within an image Select Region of Interest Functions that allow a user to select a specific region of interest in an image Creating 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 a Vision application The last step in Figure 1 1 is 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 corres
19. imagGetDistance to compute the distances between two points such as 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 IMAQ Vision for LabWindows CVI User Manual 5 26 ni com Chapter 5 Performing Machine Vision Tasks Analytic Geometry Measurements Use the following functions to make geometrical measurements from the points you detect in the image e imagFitLine Fits a line to a set of points and computes the equation of the line e imagFitCircle2 Fits a circle to a set of at least three points and computes its area perimeter and radius e imagFitEllipse2 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 e imagGetIntersection Finds the intersection point of two lines specified by their start and end points e imagGetAngle Finds the smaller angle between two lines e imaqgGetPerpendicularLine Finds the perpendicular line from a point to a line and computes the perpendicular distance between the point and the line e imagGetBisectingLine Finds the line that bisects the angle formed by two lines e imagGetMidLine Finds the line that is midway between a point and a line and is parallel to the line e imagGetPolygonArea Calculates the area of a poly
20. image but it does not modify the image The overlay appears every time you display the image in an external window National Instruments Corporation 5 31 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks Use the following functions to overlay search regions inspection results and other information such as text and bitmaps imagOverlayPoints Overlays points on an image Specify a point by its x coordinate and y coordinate imagOverlayLine Overlays a line on an image Specify a line by its start and end points imagOverlayRect Overlays a rectangle on an image imagOverlayOval Overlays an oval or a circle on the image imaqOver imaqOver imaqOver imaqOver imaqOver image imaqOver image LayArc Overlays an arc on the image layMetafile Overlays a metafile on the image LayText Overlays text on an image LayROT Overlays an ROI on an image layClosedContour Overlays a closed contour on an layOpenContour Overlays an open contour on an To use these functions 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 overlays with these functions You can configure the following processing functions to overlay different types of information on the inspection image imagF indEdge imaqFindCircularEdge imaqFindConcentri
21. 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 Finds the photometric negative of an image 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 ni com hit miss function HSI HSL HSV hue T O image image border Image Browser image buffer image definition image display environment National Instruments Corporation G 7 Glossary 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 8 bits for hue 8 bits for saturation 8 bits for luminance and 8 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 acqu
22. images and stores the result in the first source image imaqAdd myImageB myImageA myImageB This function adds two source images and stores the result in the second source image Most operations between two images require that the images have the same type and size However some arithmetic operations can work between two different types of images such as 8 bit and 16 bit images Some functions perform operations that populate an image 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 function can modify the size of an image Some functions take an additional mask parameter The presence of this parameter indicates that the processing or analysis is dependent on the contents of another image the image mask Sy Note The image mask must be an 8 bit image If you want to apply a processing or analysis function to the entire image pass NULL for the image mask Passing the same image to both the source image and image mask also gives the same effect as passing NULL for the image mask except in this case the source image must be an 8 bit image 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 IMAQ device load an image from a file stored on your computer or convert data stored in a 2D array to
23. imaqReadVisionFile 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 Now that you have calibrated your setup correctly you can apply the calibration settings to images that you acquire Use imaqCopyCalibrationInfo to attach the calibration information of the current setup to each image you acquire This function 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 Using the calibration information attached to the image you can accurately convert pixel coordinates to real world coordinates to make any of the analytic geometry measurements with imagTransformPixelToRealWorld If your application requires that you make shape measurements correct the image by removing distortion with imaqCorrectImage Ss 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 Use imaqWriteVisionFile to save the image and all of the attached calibration information to a f
24. 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 connected region or grouping of non zero pixels in a binary image A series of processing operations and analysis functions that produce some information about the particles in an image The technique used to locate quickly 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 size and the vertical size 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
25. line in the image Action Click to place a new vertex and double click to complete the ROI element Polygon Draw a polygon in the image Action Click to place a new vertex and double click to complete the ROI element IMAQ Vision for LabWindows CVI User Manual 3 2 ni com Chapter 3 Making Grayscale and Color Measurements Table 3 1 Tools Palette Functions Continued Icon Tool Name Function Freehand Line Draw a freehand line in the image Action Click the initial position drag to the desired shape and release the mouse button to complete the shape Freehand Region Draw a freehand region in the image Action Click the initial position drag to the desired shape and release the mouse button to complete the shape 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 desired position and release the mouse button to complete the pan Hold down the lt Shift gt key while drawing an ROI to constrain the ROI to the horizontal vertical or diagonal axes 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
26. 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 sensitive to changes in rotation than a template that is rotationally asymmetric Feature Detail A template with relatively coarse features is less sensitive to variations in size and rotation than a template with fine features However the template must contain enough detail to identify it Positional Information A template with strong edges in both the x and y directions is easier to locate IMAQ Vision for LabWindows CVI User Manual 5 20 ni com Chapter 5 Performing Machine Vision Tasks 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 because background
27. matches are still found using color and shape information but they are ranked based entirely on their shape scores Minimum Contrast Use the minContrast element 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 set minimum contrast value Refer to the Setting Matching Parameters and Tolerances section of this chapter for more information about minimum contrast IMAQ Vision for LabWindows CVI User Manual 5 24 ni com Chapter 5 Performing Machine Vision Tasks 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 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 imagMatchColorPattern These test images 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 Finding Points Using Color Location Color location algorithms provide a quick way to locate regions in an image with specific colors Use color loca
28. 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 Refer to Chapter 5 Image Processing of the IMAQ Vision Concepts Manual for more information about grayscale morphology transformations Use imagGrayMorphology to perform one of the following seven transformations e Erosion Reduces the brightness of pixels that are surrounded by neighbors with a lower intensity e Dilation Increases the brightness of pixels surrounded by neighbors with a higher intensity A dilation produces the opposite effect of an erosion e Opening Removes bright pixels isolated in dark regions and smooths boundaries National Instruments Corporation 2 11 IMAQ Vision for LabWindows CVI User Manual Chapter 2 FFT Getting Measurement Ready Images e Closing Removes dark pixels isolated in bright regions and smooths boundaries e Proper opening Removes bright pixels isolated in dark regions and smooths the inner contours of particles e
29. 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 National Instruments Corporation 3 13 IMAQ Vision for LabWindows CVI User Manual Performing Particle Analysis This chapter describes how to perform particle analysis on your images Use particle analysis to find statistical information about particles such as the area 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 you perform 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 to 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 b
30. search area Object positioning accuracy better than 5 degrees Build a coordinate transformation based on edge detection using two distinct search areas y Build a coordinate transformation based on pattern matching Build a coordinate transformation based on pattern matching shift invariant strategy rotation invariant strategy National Instruments Corporation Figure 5 4 Building a Coordinate Transform 5 7 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks Set Search Areas You use ROIs to define search areas in your images and limit the areas in which you perform your processing and inspection You can define ROIs interactively or programmatically Defining Regions Interactively Complete the following steps to interactively define an ROI 1 Use imaqConstructROI2 to display an image and the tools palette in a window Select an ROI tool from the tools palette Draw an ROI on your image Resize and reposition the ROI until it specifies the area you want to process Click OK to output a descriptor of the region you selected You can input the ROI descriptor into many analysis and processing functions You can also use imaqSelectRect and imagqSelectAnnulus to define ROIs Complete the following steps to use these functions 1 Call the function to display an image in a window Only the tools specific to that func
31. 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 background 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 LabWindows CVI User Manual Chapter 2 Getting Measurement Ready Images 9 3 Select an IMAQ device that meets your needs National Instruments offers several IMAQ devices including 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 a National Instruments image acquisition device configure the NI IMAQ driver software through MAX Open MAX by double clicking the Measurement amp Automation Explorer icon on your desktop Refer to the NJ IMAQ User Manual and the Measurement and 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
32. the characters inside the ROI of the image under inspection 3 Use imaqDispose to free the resources that the OCR Session used National Instruments Corporation 5 29 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks Reading Barcodes ag Use barcode reading functions to read values encoded into 1D barcodes Data Matrix barcodes and PDF417 barcodes Reading 1D Barcodes To read a 1D barcode locate the barcode in the image using one of the techniques described in this chapter Then pass the ROI Descriptor of the location into imaqReadBarcode Use imaqReadBarcode to read values encoded in the 1D barcode Specify the type of 1D barcode in the application using the type parameter 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 imaqgReadDataMatrixBarcode to read values encoded in a Data Matrix barcode The function can determine automatically 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 imagReadDataMatrixBarcode can locate automatically one or multiple Data Matrix barcodes in an image However you can improve the inspection performance by locating the barcodes using one of the techniques described in this
33. 0 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 see 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 in the image For example a technique called clamping uses edge locations to measure the width of a part You 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 Those locations can then be combined 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 vibrat
34. 00 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 transformations 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 LabWindows CVI User Manual Glossary neighbor neighborhood operations NI IMAQ 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 LabWindows CVI 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
35. Each component becomes an 8 bit or 16 bit image that you can process like any other grayscale image Using imaqReplaceColorPlanes 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 Figures 3 4 and 3 5 illustrate how a color image breaks down into its three primary components National Instruments Corporation 3 7 IMAQ Vision for LabWindows CVI User Manual Chapter 3 Making Grayscale and Color Measurements Color Image 32 Hue Saturation Intensity Hue Saturation Luminance Hue Saturation 8 bit Image Processing a Red 8 ma Green 8 ma Blue 8 a Hue 8 F Saturation or Color Fy Intensity Image im Hue 22 8 ry Saturation or Fy Luminance ma Hue 8 Ta Saturation or ma Value 8 3 IMAQ Vision for LabWindows CVI User Manual Figure 3 4 Primary Components of a 32 Bit Color Image Color Image m Red Green Blue BILS 16 ma 16 16 16 bit Image Processing 16 as 16 16 Red Green Blue Color a Image Figure 3 5 Primary Components of a 64 Bit Color Image Use imagExtractColorPlanes to extract the red green blue hue saturation intensity lumina
36. IMAQ IMAQ Vision for LabWindows CVI User Manual Wy NATIONAL August 2004 Edition p INSTRUMENTS Part Number 371266A 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 Natio
37. IVALENT_ELLIPSE_MINOR_AXIS_FERET Length of the minor axis of the ellipse with the same area as the particle and major axis equal in length to the max feret diameter IMAQ_MT_EQUIVALENT_RECT_DIAGONAL Distance between opposite corners of the rectangle with the same perimeter and area as the particle IMAQ_MT_EQUIVALENT_RECT_LONG_SIDE Longest side of the rectangle with the same perimeter and area as the particle w IMAQ_MT_EQUIVALENT_RECT_SHORT_SID Shortest side of the rectangle with the same perimeter and area as the particle IMAQ_MT_EQUIVALENT_RECT_SHORT_SIDE_FERET Shortest side of the rectangle with the same area as the particle and longest side equal in length to the max feret diameter IMAQ_MT_ELONGATION_FACTOR Max feret diameter divided by equivalent rectangle short side feret IMAQ_MT_FIRST_PIXEL_X X coordinate of the highest leftmost particle pixel IMAQ_MT_FIRST_PIXEL_Y Y coordinate of the highest leftmost particle pixel IMAQ_MT_HU_MOMENT_1 First Hu moment IMAQ_MT_HU_MOMENT_2 Second Hu moment IMAQ_MT_HU_MOMENT_3 Third Hu moment IMAQ_MT_HU_MOMENT_4 Fourth Hu moment IMAQ Vision for LabWindows CVI User Manual 4 6 ni com Chapter 4 Performing Particle Analysis Table 4 1 Particle Measurements Continued Measurement Description IMAQ_MT_HU_MOMENT_5 Fifth Hu mom
38. LLS ay Note Setting By default imaqReadDataMatrixBarcode assumes the shape of the barcode is square If the shape of your barcode is rectangular set the barcodeShape element of the options parameter to IMAQ_RECTANGULAR_BARCODE_2D the barcodeShape element to IMAQ_RECTANGULAR_BARCODE_2D when the barcode you need to read is square reduces the reliability of your application By default imaqReadDataMatrixBarcode automatically detects the type of barcode to read You can improve the performance of the your function 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 Use imaqReadPDF417Barcode to read values encoded in a PDF417 barcode imagReadPDF417Barcode can locate automatically 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 this chapter Then pass in the ROI location to imaqReadPDF417Barcode Tip If you need to read only one barcode per image set the searchMode parameter to IMAQ_SEARCH_SINGLE_CONSERVATIVE to increase the speed of your application Display Results You can overlay the results obtained at various stages of you inspection process on the window that displays your inspection image The software attaches the information that you want to overlay to the
39. THE SUITABILITY 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 EoI AEI EOI ARR EAE E E E E AE E E E E ix Related Doc umentatioi nissin nnna E E E E A x IMAO V Biomi tnae okt BBY a a a n a a a Raed ease x NI Vision ASsistant cccccccssscccccsssscccccsseseeeccesssseecceeessseeeceeessseeeceeesseeeceeens x NI Vision Builder for Automated Inspection sesssseseesessessseseessessressessessrese x Other Documentation ccccccccccessscccceeesscecceesessseeeceesssseeeceesesseeeceeesssseeceeens xi Chapter 1 Introduction to IMAQ Vision A DOU IMAG VIS Olm senna e ea apis ohh eee T N S 1 1 Application Development Environments sssesssssssssessessresrrsstsstesressrssessessrssreseesses 1 1 IMAQ Vision Function Tree cccccscccccessssscecceesssseececessssceecceesssseeeceesssseeeeeeessseeeeeens 1 2 IMAQ Machine Vision Function Tree ccccceccsscccssseecesseeesseeeessneeesseeeseneeessneeessaeens 1 3 Creating IMAQ Vision Applications 0 0 eee eee eeeeeeeeseceeeeseeseesseeaeenseeaeeneeeaesneseaeenees 1 4 Chapter 2 Getting Measurement Ready Images Set Up Your Imaging System 0 eee cece eeceseeeeceseceeeeseseeeesecseeeaeceeeeaesnseeaesneeeneenaes 2 1 Calibrate Your Imaging System eee eseeeese
40. TION 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
41. The measurement points you located with edge detection and pattern matching are in pixel coordinates If you need to make measurements using real world units use imaqTransformPixelToRealWorld to convert the pixel coordinates into real world units Make Measurements You can make different types of measurements either directly from the image or from points that you detect in the image Distance Measurements Use the following functions to make distance measurements for your inspection application Clamp functions measure the separation between two edges in a rectangular search region First clamp functions detect points along the two edges using the Rake function Then they compute the distance between the points detected on the edges along each search line of the rake and return the largest or smallest distance The imaqSelectRect function generates a valid input search region for these functions You also need to 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 These functions work directly on the image under inspection and they output the coordinates of all the edge points that they find The following list describes the available clamp functions e imagClampMax Measures the largest separation between two edges in a rectangular search region e imagClampMin Finds the smallest separation between two edges Use
42. ad of using an ROI These functions determine the edge points based on their contrast and slope You can specify whether you want to find the edge points using subpixel accuracy Finding Edge Points Along Multiple Search Contours Use imagRake imaqSpoke and imagqConcentricRake to find edge points along multiple search contours These functions behave similar to imaqEdgeToo12 but they find edges on multiple contours Pass in an ROI to define the search region for these functions The imagRake function 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 The imagSpoke function 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 The imaqConcentricRake function works on an annular search region The concentric rake is an adaptation of the Rake to an a
43. agCountParticles to return specific measurements of a particle Table 4 1 lists all of the measurements that imaqMeasureParticle returns Table 4 1 Particle Measurements Measurement Description IMAQ MT AREA Area of the particle IMAQ_MT_AREA_BY IMAGE AREA Percentage of the particle area covering the image area IMAQ_MT_AREA_BY_PARTICLE_AND_HOLES_AREA Percentage of the particle area in relation to the area of its particle and holes IMAQ_MT_AVERAGE_HORIZ_SEGMENT_LENGTH Average length of a horizontal segment in the particle IMAQ_MT_AVERAGE_V ERT_SEGMENT_LENGTH Average length of a vertical segment in the particle IMAQ_MT_BOUNDING_RECT_BOTTOM Y coordinate of the lowest particle point IMAQ_MT_BOUNDING_RECT_TOP Y coordinate of the highest particle point IMAQ Vision for LabWindows CVI User Manual 4 4 ni com Chapter 4 Performing Particle Analysis Table 4 1 Particle Measurements Continued IMAQ_MT_BOUNDING_RI Measurement Description IMAQ_MT_BOUNDING_RECT_LEFT X coordinate of the leftmost particle point IMAQ_MT_BOUNDING_RECT_RIGHT X coordinate of the rightmost particle point IMAQ_MT_BOUNDING_RECT_HEIGHT Distance between the y coordinate ECT_WIDTH of highest particle point and the y coordinate of the lowest particle point Distance between the x coordinate of
44. an image Functions that acquire images load images from file or convert data from a 2D array to an image automatically allocate the memory space required to accommodate the image data National Instruments Corporation 2 5 IMAQ Vision for LabWindows CVI User Manual Chapter 2 Getting Measurement Ready Images Acquiring an Image Use one of the following methods to acquire images with a National Instruments IMAQ device Acquire a single image using imaqgEasyAcquire When you call this function it initializes the IMAQ device and acquires the next incoming video frame Use this function for low speed single capture applications where ease of programming is essential Acquire a single image using imaqSnap When you call this function it acquires the next incoming video frame on an IMAQ device you have already initialized using imgInterfaceOpen and imgSessionOpen Use this function for high speed single capture applications Acquire images continually through a grab acquisition Grab functions perform high speed acquisitions that loop continually on one buffer Use imaqgSetupGrab to start the acquisition Use imagGrab to return a copy of the current image Use imaqStopAcquisition to stop the acquisition Acquire a fixed number of images using a sequence acquisition Set up the acquisition using imaqSetupSequence Use imagStartAcquisition to acquire the number of images you requested during setup If you want to acq
45. anual G 4 ni com edge steepness energy center equalize function erosion exponential and gamma corrections exponential function FFT fiducial Fourier transform frequency filters ft function G gamma gradient convolution filter National Instruments Corporation G 5 Glossary The number of pixels that corresponds to the slope or transition area of an edge The center of mass of a grayscale image See also center of mass See histogram equalization 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 s 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 The nonlinear change in the difference between the video signal s bright
46. ap 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 LabWindows CVI User Manual G 2 ni com C caliper center of mass chroma chromaticity closing clustering CLUT color image color space complex image connectivity National Instruments Corporation G 3 Glossary 1 A function in the NI Vision Assistant and in NI Vision Builder for Automated Inspection that calculates distances angles circular fits and the center of mass based on positions given by edge detection particle analysis centroid and search functions 2 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 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 saturati
47. arch Area 4 Measurement Area Figure 5 3 Locating Coordinate System Axes with Two Search Areas 2 Use the options parameter to choose the options you need to locate the edges on the object the coordinate system axis direction and the results that you want to overlay onto the image Set the options parameter to NULL to use the default options 3 Choose the mode for the function To build a coordinate transform for the first time set the mode parameter to IMAQ_FIND_REFERENCE To update the coordinate transform in subsequent images set this mode to IMAQ_UPDATE_TRANSFORM National Instruments Corporation 5 5 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks Using Pattern Matching to Build a Coordinate Transform You can build a coordinate transform using pattern matching Use imagFindTransformPattern to define a coordinate system based on the location of a reference feature Use this technique when the object under inspection does not have straight distinct edges Complete the following steps to build a coordinate reference system using pattern matching 3 Note The object may 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 of this chapter for more information about defining a templa
48. asurements Chapter 6 Mee Classify Machine Objects Characters Symbologies Vision Convert Pixel Coordinates to i Real World Coordinates 1 Make Measurements Display Results Figure 1 2 Inspection Steps for Building a Vision Application A Note Diagram items enclosed with dashed lines are optional steps IMAQ Vision for LabWindows CVI User Manual 1 6 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 How 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 your 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
49. ation compared to an erosion or open operation Consider using an erosion or open operation if speed is an issue with your application Improving Particle Shapes Use imaqFillHoles to fill holes in the particles Use imaqMorphology to perform a variety of operations on the particles You can use the IMAQ_AUTOM IMAQ_CLOSE IMAQ_PCLOSE IMAQ_OPEN and IMAQ_POPEN methods to smooth the boundaries of the particles Open and proper open smooth the boundaries of the particle by removing small National Instruments Corporation 4 3 IMAQ Vision for LabWindows CVI User Manual Chapter 4 Performing Particle Analysis isthmuses while close widens the isthmuses Close and proper close fill small holes in the particle Auto median removes isthmuses and fills holes Refer to Chapter 9 Binary Morphology of the IMAQ Vision Concepts Manual for more information about these methods 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 functions to perform particle measurements e imaqCountParticles This function returns the number of particles in an image and calculates various measurements for each particle e imagMeasureParticle This function uses the calculations from im
50. brary require one or more image pointers The number of image pointers a function takes depends on the image processing function and the type of image you want to use Some IMAQ Vision functions act directly on the image and require only one image pointer Other functions that process the contents of images require pointers to the source image s and to a destination image At the end of your application dispose of each image that you created using imaqDispose National Instruments Corporation 2 3 IMAQ Vision for LabWindows CVI User Manual Chapter 2 Getting Measurement Ready Images Source and Destination Images Some IMAQ Vision functions that modify the contents of an image have source image and destination image input parameters The source image receives the image to process The destination image receives the processing results The destination image can receive either another image or the original depending on your goals If you do not want the contents of the original image to change use separate source and destination images If you want to replace the original image with the processed image pass the same image as both the source and destination Depending on the function the image type of the destination image can be the same or different than the image type of the source image The function descriptions in the IMAQ Vision for LabWindows CVI Function Reference include the type of images you can use as image inputs and outp
51. cEdge imaqClampMax imaqClampMin imaqFindPattern imaqCountObjects imaqFindTransformRect imaqFindTransformRects imagqFindTransformPattern IMAQ Vision for LabWindows CVI User Manual 5 32 ni com Chapter 5 Performing Machine Vision Tasks The following list contains the kinds of information you can overlay with the previous functions except imaqFindPattern imaqCountObjects and imagFindTransformPattern e The search area input into the function e The search lines used for edge detection e The edges detected along the search lines e The result of the function With imaqFindPattern imaqCountObjects and imagFindTransformPattern you can overlay the search area and the result Select the information you want to overlay by setting the element that corresponds to the information type to TRUE in the options input parameter Use imaqClearOverlay to clear any previous overlay information from the image Use imaqwWriteVisionFile to save an image with its overlay information to a file You can read the information from the file into an image using imagReadVisionFile Sy 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 Vision for LabWindows CVI User Manual Calibrating Images This chapter describes how to calibrate your imaging system save calibratio
52. causssventecet eae 3 1 Defining Regions Interactively eee eee seeeseeseeeseeneceeeeseeeseceensesseeeaeesees 3 1 Tools Palette Transformation 0 ccc ceeesecseeeeeeeceeeceeeeeeeseeeaees 3 5 Defining Regions Programmatically eee eseceeeeseeseeeseeeseeseseeeeaeenees 3 6 Defining Regions with MaskS 00 ce eieeeeseceeeeeeseeeseeeeeseeseeeseceensesseseaeesees 3 6 Measure Grayscale Statistics ysis sca ceccsscok tesa teet seats sues eaeteeessdens tenes E a 3 7 Measure Color Statisticss Ac Actas ea inh elie k nee ek aaa 3 7 Comparing Colors eer secs tresses ceaug e RE E vp E EEEE EA 3 9 Learning Color Information sssesseseeeseseeeesesrertsrsrtssestsrstssrsrenrsesterrsresresest 3 9 Specifying the Color Information to Learn sseseseesseeseseeseeerseeeene 3 9 Choosing a Color Representation Sensitivity seseseseesseerserereeeseee 3 12 Ignoring Learned Colors eseseeseesseesresrsrrsrsresresrsresteersreernresresrsese 3 13 Chapter 4 Performing Particle Analysis Createa Binary Images i a R E O E A 4 1 Improve the Binary Mase ss sss ccastess tees veers heen carts tenes cat aaa eatte sven vetevios 4 2 Removing Unwanted Particles cei eeeeseeeeeeseeseceseeseceseeseeesecseeesesseseaeesees 4 3 Separating Touching Particles semoir rrene eane PEE EEE ES E EE Ge 4 3 Improving Particle Shapes nienie a e o E E R KERA 4 3 Make Particle Measurement 20 0 0 eee onne r an E Ea a Ss 4 4 Chapter 5 Performing Mach
53. ceeceseeeeeesecesecseeeaeeeessecseeesecseseaseeeeaes 2 2 Create an Tima gece aaea 8 oh visage RS acti ated es sn RO ee es 2 2 Source and Destination Images 0 eee eee eeseesceeseeneceseeseeneeeaeseeeeaeeeaeeseeeees 2 4 Acquire or Read anim age x esieccegecetiv tiie i a OE aE S aA EA 2 5 ACQUITING AN TMA SE i e raees e e E E a cea E EEE EEEE ES rE OET 2 6 Reading a Filenin maa a Henin ee Sa t 2 6 Converting an Array to an mage e seesseeeeseeressssersresreresrerrsreerresresrsresresestse 2 7 Display an Jmag nii a are E E e TNE aA EA A a 2 7 Attach Calibration Information peser eee eeeesececcesecseeeseceeeeseeseeeseesecesecaeeneeeaeseeeeaeenaes 2 8 Analyze anma genian nr a Nees Wilda ila a Re 2 8 Trmiprove am Image nitions e a bates sovacavees stuacevevangesiUaveoutestdeues steve E 2 9 Lookup Tables at cncccd titin Masai eh ide Agia O ties 2 10 NCCI vases ee O D AE PEE EEN EIEEE EET 2 10 Convolution Filters scisnciiaiian a a aa ETRE 2 11 Nth Order Filtet aerei lee E cin etn een ene 2 11 Grayscale Morphol fyssan nnna e lakes eager a aa 2 11 ET E EE E T T E E EE ER A E cet ete eee 2 12 Complex Image Operations sesseesssesseresesreresrestsrrsrsresrssesreserersresrse 2 13 National Instruments Corporation v IMAQ Vision for LabWindows CVI User Manual Contents Chapter 3 Making Grayscale and Color Measurements Define R gions of Interest cesses ssccvanscasssescaecsesceteneceseedisdscaapecteueesteaqssy sca destia
54. chPattern2 6 Verify the results using a ranking method Defining and Creating Good Template Images 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 These factors are critical in creating a template image symmetry feature detail positional information and background information National Instruments Corporation 5 13 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks Symmetry A rotationally symmetric template shown in Figure 5 7a is less sensitive to changes in rotation than one that is rotationally asymmetric shown in Figure 5 7b A rotationally symmetric template provides good positioning information but no orientation information Figure 5 7 Symmetry Feature Detail A template with relatively coarse features shown in Figure 5 8a is less sensitive to variations in size and rotation than a model with fine features Figure 5 8b However the model must contain enough detail to identify the feature Figure 5 8 Feature Detail IMAQ Vision for LabWindows CVI User Manual 5 14 ni com Chapter 5 Performing Machine Vision Tasks Positional Information A template with strong edges in both the x and y directions is easier to locate Figur
55. chapter Then pass the ROI indicating the location into imaqReadDataMatrixBarcode Tip If you need to read only one barcode per image set the searchMode element of the options parameter to IMAQ_SEARCH_SINGLE_CONSERVATIVE to increase the speed of your application If the barcode occupies a large percentage of your search region has clearly defined cells and exhibits little or no rotation you can further increase the speed of your application by setting the searchMode element of the options parameter to IMAQ_SEARCH_SINGLE_AGGRESSIVE By default imaqgReadDataMatrixBarcode detects whether 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 by setting the contrast element of the options parameter to IMAQ_BLACK_ON_WHITE_BARCODE or IMAQ_WHITE_ON_BLACK_BARCODE IMAQ Vision for LabWindows CVI User Manual 5 30 ni com Chapter 5 Performing Machine Vision Tasks By default imagReadDataMatrixBarcode assumes the barcode cells are square If the barcodes you need to read have round cells set the cellShape element of the options parameter to IMAQ_ROUND_CELLS ay 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 cel1 Shape to IMAQ_SQUAR E_ CE
56. coordinates This allows you to compensate for perspective and nonlinear errors inherent in your imaging system Perspective errors occur when your camera axis is not perpendicular to the object under inspection Nonlinear distortion may occur from aberrations in the camera lens 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 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 For detailed information about calibration refer to Chapter 5 Performing Machine Vision Tasks Create an Image To create an image in IMAQ Vision for LabWindows CVI call imagCreateImage This function returns an image reference you can use when calling other IMAQ Vision functions The only limitation to the size and number of images you can acquire and process is the amount of memory on your computer When you create an image specify the type of the image Table 2 1 lists the valid image types IMAQ Vision for LabWindows CVI User Manual 2 2 ni com Chapter 2 Getting Measurement Ready Images Table 2 1 IMAQ Vision for LabWindows CVI Image Types Value Description IMAQ_IMAGE_U8 8 bits per pixel unsigned standard monochrome
57. cy 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 imagAttenuate or imagTruncate 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 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 IMAQ Vision for LabWindows CVI User Manual 2 12 ni com 3 Chapter 2 Getting Measurement Ready Images attenuation increases This operation 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 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 Lowpass truncation Frequency components above the ideal cutoff frequency are removed and the frequencies below it remain unaltered Highpass truncation Frequency components above the ideal cutoff frequency remain unaltered and the frequencies below it are removed To transform your image back to t
58. 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 1 The origin is placed at the center of the left topmost dot in the calibration grid 2 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 3 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 LabWindows CVI User Manual Chapter 6 Calibrating Images P TENN peeoeoeee eooeoeee0e EEEE H U E E E E e2e e0e0 0 y 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 A Note Ifyou 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 set 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 conver
59. dinate transform using two edge detection techniques Use imagFindTransformRect to define a coordinate system using one rectangular region Use imaqFindTransformRects to define a coordinate system using two independent rectangular regions Follow these steps to build a coordinate transform using edge detection 3 Note To use this technique the object cannot rotate more than 65 in the image 1 Specify one or two rectangular ROIs a Ifyouuse imaqFindTransformRect 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 A t p i 1 Search Area for the Coordinate System 3 Origin of the Coordinate System 2 Object Edges 4 Measurement Area Figure 5 2 Coordinate Systems of a Reference Image and Inspection Image IMAQ Vision for LabWindows CVI User Manual 5 4 ni com Chapter 5 Performing Machine Vision Tasks b If you use imagFindTransformRects specify two rectangular objects 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 1 Primary Search Area 3 Origin of the Coordinate System 2 Secondary Se
60. ding 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 part surfaces Analyzes groups of pixels within an image and returns information about the size shape position and pixel connectivity Typical applications include 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 from a programming language to a VI in LabVIEW The sum of the Red Green and Blue primary colors divided by three Red Green Blue 3 IMAQ Vision for LabWindows CVI User Manual G 8 ni com intensity calibration intensity profile intensity range intensity threshold jitter JPEG K kernel L labeling LabVIEW LabWindows CVI National Instruments Corporation G 9 Glossary Assigns user defined quantities such as optical densities or concentrations to the gray level values in an image The gray level distrib
61. e 5 9a shows good positional information in both the x and y directions while Figure 5 9b shows insufficient positional information in the y direction Figure 5 9 Positional Information Background Information Unique background information in a template improves search performance and accuracy Figure 5 10a shows a pattern with insufficient background information Figure 5 10b illustrates a pattern with sufficient background information Figure 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 imagLearnPatternz2 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 then the pattern matching algorithm has to learn only those features from National Instruments Corporation 5 15 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks the template that are necessary for shift invariant matching However if you want to match the template at any orientation use rotation invariant matching Use the learningMode parameter of imaqhearnPattern2 to specify which type of learning mode to use The learning process is usually time intensive because the algorithm attempts to find the optim
62. e detection 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 two dimensional representation of the impulse response of the filter that they represent Similar to the distance functions but with more accurate results 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 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 and the average pixel intensity after the edge Any of several techniques to identify the edges of objects in an image IMAQ Vision for LabWindows CVI User M
63. e following steps to use these functions 1 Call the function to display an image in an ROI Constructor window Only the tools specific to that function are available for you to use 2 Draw an ROI on your image Resize or reposition the ROI until it covers the area you want to process IMAQ Vision for LabWindows CVI User Manual 3 4 ni com Chapter 3 Making Grayscale and Color Measurements 3 Click OK to populate a structure representing the ROI You can use this structure as an input to a variety of functions such as the following functions that measure grayscale intensity imaqLightMeterPoint Uses the output of imaqSelec tPoint imaqLightMeterLine Uses the output of imaqSelec thine imaqLightMeterRect Uses the output of imaqSelec tRect Tools Palette Transformation The tools palette shown in Figure 3 3 automatically transforms from the palette on the left to the palette on the right when you manipulate an ROI tool in an image window The palette on the right displays the characteristics of the ROI you are drawing ae IMAQ Tools E3 IMAQ Tools E3 194 8 Bit Image 8 Bit Image xX 386 26 x 501 Me ES I Z Pixel Intensity Image type indicator 8 bit 16 bit Float RGB HSL Complex Coordinates of the mouse on the active image window Anchoring coordinates of a Region of Interest Size of an active Region of Interest Length and ho
64. e image Reject particles on the border of the image when you suspect that the information about those particles is incomplete Use imaqSizeFilter to remove large or small particles that do not interest you You can also use the IMAQ_ ERODE IMAQ_OPEN and IMAQ_POPEN methods in imaqMorphology to remove small particles Unlike imagSizeFilter these three operations alter the size and shape of the remaining particles Use the IMAQ_HITMISS method of imaqMorphology to locate particular configurations of pixels which you define with a structuring element Depending on the configuration of the structuring element the IMAQ_HITMISS method 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 keep use imagParticleFilter2 to filter out particles that do not interest you Separating Touching Particles Use imaqSeparation or apply an erosion or an open operation with imagMorphology to separate touching objects The imaqSeparation function is an advanced function that separates particles without modifying their shapes However erosion and open operations alter the shape of all the particles ay Note A separation is a time intensive oper
65. e that completely covers the image IMAQ_MT_RATIO_OF_EQUIVALENT_ELLIPSE_AXES Equivalent ellipse major axis divided by equivalent ellipse minor axis IMAQ_MT_RATIO_OF_EQUIVALENT_RECT_SIDES Equivalent rectangle long side divided by equivalent rectangle short side IMAQ_MT_SUM_X Sum of all x coordinates in the particle IMAQ_MT_SUM_Y Sum of all y coordinates in the particle National Instruments Corporation 4 9 IMAQ Vision for LabWindows CVI User Manual Chapter 4 Performing Particle Analysis Table 4 1 Particle Measurements Continued Measurement Description IMAQ_MT_SUM_xXx Sum of all x coordinates squared in the particle IMAQ_MT_SUM_XY Sum of all x coordinates multiplied by y coordinates in the particle IMAQ_MT_SUM_YY Sum of all y coordinates squared in the particle IMAQ_MT_SUM_XXX Sum of all x coordinates cubed in the particle IMAQ_MT_SUM_XXY Sum of all x coordinates squared multiplied by y coordinates in the particle IMAQ_MT_SUM_XYY Sum of all x coordinates multiplied by y coordinates squared in the particle IMAQ_MT_SUM_YYY Sum of all y coordinates cubed in the particle IMAQ_MT_TYPE_FACTOR Factor relating area to moment of inertia IMAQ_MT_WADDEL_DISK_DIAMETER Diameter of a disk with the same area as the particle IMAQ Vision for LabWindows CVI User Manual 4 1
66. ected In no event shall National Instruments be liable for any damages arising out of or related to this document or the information contained in it EXCEPT AS SPECIFIED HEREIN NATIONAL INSTRUMENTS MAKES NO WARRANTIES EXPRESS OR IMPLIED AND SPECIFICALLY DISCLAIMS ANY WARRANTY OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE CUSTOMER S RIGHT TO RECOVER DAMAGES CAUSED BY FAULT OR NEGLIGENCE ON THE PART OF NATIONAL INSTRUMENTS SHALL BE LIMITED TO THE AMOUNT THERETOFORE PAID BY THE CUSTOMER NATIONAL INSTRUMENTS WILL NOT BE LIABLE FOR DAMAGES RESULTING FROM LOSS OF DATA PROFITS USE OF PRODUCTS OR INCIDENTAL OR CONSEQUENTIAL DAMAGES EVEN IF ADVISED OF THE POSSIBILITY THEREOF This limitation of the liability of National Instruments will apply regardless of the form of action whether in contract or tort including negligence Any action against National Instruments must be brought within one year after the cause of action accrues National Instruments shall not be liable for any delay in performance due to causes beyond its reasonable control The warranty provided herein does not cover damages defects malfunctions or service failures caused by owner s failure to follow the National Instruments installation operation or maintenance instructions owner s modification of the product owner s abuse misuse or negligent acts and power failure or surges fire flood accident actions of third parties or other events outside reasonable contro
67. eed Note Use the IMAQ_CONSERVATIVE Strategy if you have multiple targets located very close to each other in the image e IMAQ BALANCED Uses values in between the IMAQ AGGRESSIVE and IMAQ_ CONSERVATIVE strategies e IMAQ AGGRESSIVE Uses a large step size a lot of sub sampling and all of the color information from the template IMAQ 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 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 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 its shape information set the weight higher For example if you set colorwWeight to 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 you set colorWeight to 0 the
68. eeeeeeereeee 5 19 Finding Points Using Color Pattern Matching 0 eee eee eeeeneeeeeeeeees 5 19 Defining and Creating Good Color Template Images 0 5 20 Training the Color Pattern Matching Algorithm ee 5 21 Defining a Search Areare niont ain iia 5 22 Setting Matching Parameters and Tolerances sessereeeeeeeeereesee 5 23 Testing the Search Algorithm on Test Images eee eens 5 25 Finding Points Using Color Location eecceseseecesecseeeseeseeeseeeenneeaes 5 25 Convert Pixel Coordinates to Real World Coordinates eee eeceeeeeeeseeeeeseeeeetaees 5 26 Make Measurements iiser a a AA Revi cules E a A a e ean ieia 5 26 Distance Meas reM ntSv s issii iiio atiaeina iner aesan aE aai 5 26 Analytic Geometry Measurements 20 0 0 eee ceceeeeceeeseceeeseeeeseeseeseeeasenseeaeenes 5 27 Instrument Reader Measurement eee eceeseeeseeseeseeeseceeceseeseeesesseseneesees 5 27 Identify Parts Under Inspection 0 eee ee eee essceceseeeeeeseceeeesecseeeaeeecesecaeensesseeneesaeenaes 5 28 Classifying Samples si 3 csesteseetestscecesdvesatse eara naa ioeie ia eeii ieia 5 28 Reading Charactets Asirienii annene oE EE EE T Reais 5 29 Reading Barcodes s csesvzoshesieleessassessuacabead iara E EE T 5 30 Reading 1D Barcodes i2 ccceeae at iddeniiten e a a a 5 30 Reading Data Matrix Barcodes sssseesseeesserereeesreeresrsresrsresresesreses 5 30 Reading PDF417 Barcodes s sssesssesseeesseersrestsrrs
69. ent IMAQ MT _HU_ MOMENT _6 Sixth Hu moment IMAQ_MT_HU_MOMENT_7 Seventh Hu moment IMAQ_MT_HEYWOOD_CIRCULARITY_FACTOR Perimeter divided by the circumference of a circle with the same area IMAQ_MT_HOLES_PERIMETER Sum of the perimeters of each hole in the particle IMAQ_MT_HYDRAULIC_RADIUS Particle area divided by the particle perimeter IMAQ_MT_HOLES_AREA Sum of the areas of each hole in the particle IMAQ_MT_IMAGE_AREA Area of the image IMAQ MT MAX FERET DIAMETER Distance between the start and end of the line segment connecting the two perimeter points that are the furthest apart IMAQ_ MT_MAX_ FERET DIAMETER_END_xX X coordinate of the end of the line segment connecting the two perimeter points that are the furthest apart IMAQ_ MT_MAX FERET DIAMETER_END_Y Y coordinate of the end of the line segment connecting the two perimeter points that are the furthest apart IMAQ_ MT_MAX_ FERET DIAMETER_ORIENTATION Angle of the line segment connecting the two perimeter points that are the furthest apart IMAQ_ MT_MAX FERET DIAMETER_START_X X coordinate of the start of the line segment connecting the two perimeter points that are the furthest apart National Instruments Corporation 4 7 IMAQ Vision for LabWindows CVI User Manual Chapter 4 Performing Par
70. eo a b c Figure 6 5 Types of Image Distortion IMAQ Vision for LabWindows CVI 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 mode element of the options parameter to IMAQ_ PERSPECTIVE to choose the perspective calibration algorithm Learning and applying perspective projection is less computationally intensive than the nonlinear method However perspective projection cannot handle 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 mode element of the options parameter to IMAQ_ NONLINEAR to choose the nonlinear calibration algorithm 1 Calibration ROI Using the Perspective Algorithm 2 Calibration ROI Using the Nonlinear Algorithm Figure 6 6 Calibration ROIs Using the Learning Score The learning process returns a score that reflects how well the software learned the input image A learning score above 800 indicates that you c
71. er session used IMAQ Vision for LabWindows CVI User Manual 5 28 ni com Chapter 5 Performing Machine Vision Tasks The following code sample provides an example of a typical classification application ClassifierSession session Image image ROI roi char fileName The classifier file to use ClassifierReport report session imaqReadClassifierFile NULL fileName IMAQ CLASSIFIER READ ALL NULL NULL NULL while stillClassifying Acquire and process an image and store it in the image variable Locate the object to classify and store an ROI containing that object in the roi variable report imaqClassify image session roi NULL 0 Take action based on the report imaqDispose report imaqDispose session 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 OCR Training Interface After you have trained samples of the characters you want to read use the following functions to read the characters 1 Use imaqReadOCRFile to read in a session that you created using the NI OCR Training Interface 2 Use imaqReadText to read
72. etting Measurement Ready Images Attach Calibration Information If you want to attach the calibration information of the current setup to each image you acquire use imaqCopyCalibrationInfo This function takes in a source image 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 For detailed information about calibration refer to Chapter 6 Calibrating Images Sy 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 imaqwriteVisionFile to save the image and all of the attached calibration information to a file Analyze an Image After you acquire and display an image you may want to analyze the contents of the image for the following reasons e To determine whether the image quality is high enough 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 Use imaqHistogram 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 cont
73. gon specified by its vertex points Instrument Reader Measurements You can make measurements based on the values obtained by meter and LCD readers Use imaqGetMeterArc to calibrate a meter or gauge that you want to read The imaqGetMeterArc function calibrates the meter using one of two modes The IMAQ_METER_ARC_ROI mode uses the initial position and the full scale position of the needle When using this mode the function calculates the position of the base of the needle and the arc traced by the tip of the needle The IMAQ_ METER _ARC_POINTS mode 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 When using this mode the function calculates the position of the points along the arc covered by the tip of the needle Use imagReadMeter 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 National Instruments Corporation 5 27 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks Use imagFindLCDSegments 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 imagReadLCD to read multiple digits of an LCD or LED Identify Parts Under Inspection In addition to making measurement
74. he 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 VI which consists of a front panel user interface and a block diagram program National Instruments Corporation G 17 IMAQ Vision for LabWindows CVI User Manual Index Numerics 1D barcodes reading 5 30 2D arrays converting to images 2 5 2 7 A acquiring images 2 5 analyzing components of color images 3 7 images 2 8 particles 4 1 applications creating Vision 1 4 applying LUTs 2 10 applying to images 2 10 arrays converting planes of complex images to arrays 2 13 attaching calibration information 6 10 calibration information to images 2 8 attenuation highpass 2 13 lowpass 2 12 barcodes reading 1D barcodes 5 30 reading data matrix barcodes 5 30 reading PDF417 barcodes 5 31 binary images creating 4 1 improving 4 2 National Instruments Corporation C calibrating images 6 1 imaging systems 2 2 calibration defining templates 6 2 saving calibration information 6 10 using simple calibration 6 9 calibration information attaching 6 10 attaching to images 2 8 learning 6 5 saving 6 10 calibration templates defining 6 2 calibrations invalidating
75. he spatial domain use imaqinverseFFT Complex Image Operations The imagqExtractComplexPlane and imaqReplaceComplexPlane functions allow you to access process and update independently the real and imaginary planes of a complex image You can also convert planes of a complex image to an array and back with imaqComplexPlaneToArray and imagArrayToComplexPlane National Instruments Corporation 2 13 IMAQ Vision for LabWindows CVI User Manual 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 to Taking Grayscale and Color Measurements Define Regions of Interest A region of interest ROI is an area of an image in which you want to focus your image analysis You can define an ROI interactively programmatically or with an image mask Defining Regions Interactively You can interactive
76. her in the color space Use the sensitivity parameter of imaqLearnColor to 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 IMAQ Vision for LabWindows CVI User Manual 3 12 ni com 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 matching 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 other non background 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
77. hose the appropriate learning algorithm that the grid image complies with the guideline and that your vision system setup is adequate Sy Note A high score does not reflect the accuracy of your system National Instruments Corporation 6 7 IMAQ Vision for LabWindows CVI 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 the range parameter 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 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 learnMap element of the options parameter to TRUE to learn the error map Learning the Correction Table If the speed of image correction is a critical factor for your application use a correction table The correction table is a lookup table stored
78. ile IMAQ Vision for LabWindows CVI User Manual 6 10 ni com Technical Support and Professional Services Visit the following sections of the National Instruments Web site at ni com for technical support and professional services e Support Online technical support resources at ni com support include the following Self Help Resources For immediate 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 programs 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 e 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 e System Integration If 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 c
79. image into other grayscale values in the transformed image IMAQ Vision provides four functions that directly or indirectly apply lookup tables to images imagMathTransform Converts the pixel values of an image by eplacing them with values from a predefined lookup table IMAQ Vision has seven predefined lookup tables based on mathematical transformations For more information about these lookup tables refer to Chapter 5 Image Processing of the IMAQ Vision Concepts Manual e imaqLookup Converts the pixel values of an image by replacing them with values from a user defined lookup table e imagEqualize Distributes the grayscale values evenly within a given grayscale range Use imaqEqualize to increase the contrast in images containing few grayscale values imaqInverse Inverts the pixel intensities of an image to compute the negative of the image For example use imaqInverse before applying an automatic threshold to your image if the background pixels are brighter than the object pixels Filter your image when you need 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 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 imagLowPass or define your own lowpa
80. 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 such as between 15 to 15 provide this restriction information to the pattern matching algorithm in the angleRanges element of the imaqMatchPattern2 options parameter This information improves your search time because the pattern matching algorithm looks for the pattern at fewer angles Refer to Chapter 12 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 imaqMatchPattern2 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 IMAQ Vision for LabWindows CVI User Manual 5 18 ni com Chapter 5 Performing Machine Vision Tasks Using a Ranking Method to Verify Results The manner in which you interpret the pattern matching algorithm depends on y
81. 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 learnTable element of the options parameter to TRUE to learn the correction table Setting the Scaling Method Use the method element of the options parameter to choose the appearance of the corrected image Select either IMAQ_ SCALE _TO_FIT or IMAQ_SCALE_TO_PRESERVE_AREA Refer to Chapter 3 System Setup and Calibration of the IMAQ Vision Concepts Manual for more information about the scaling methods Calibration Invalidation Any image processing operation that changes the image size or orientation voids the calibration information in a calibrated image Examples of functions that void calibration information include imagResample imaqScale imaqArrayToImage and imaqUnwrap IMAQ Vision for LabWindows CVI User Manual 6 8 ni com Chapter 6 Calibrating Images Simple Calibration When the axis of your camera is perpendicular to the image plane and lens distortion is negligible use simple calibration In simple calibration a pixel coordinate is transformed to a real world coordinate through scaling in the horizontal and vertical directions Use simple calibration to map pixel coordinates to real world coordinates directly without a calibra
82. ine Vision Tasks Locate Objects to Inspetti nanoen nta e a e eae E E ease dade 5 2 Using Edge Detection to Build a Coordinate Transform eee 5 4 Using Pattern Matching to Build a Coordinate Transform eee 5 6 Choosing a Method to Build the Coordinate Transform eee 5 7 Set Search Areas soc ee eek sti rasp neta ativan in Raed eee aeeey 5 8 Defining Regions Interactively eee esseeeseeseeeseeseeneeeseeeseceeeseeseeeaeesees 5 8 Defining Regions Programmatically eee eseceeeseeseeeseceeeeseeneeeaeenees 5 9 Pind Measuiremiont POTS iscsi e n E R eect ova ceeeuetes dete etek soa EE S 5 9 Finding Features Using Edge Detection eee eseeseeseceeeeeeneeeseeeeaes 5 9 Finding Lines or Circles cvccccdesasecevecuieseteveceatbecdecdh cntvpevesdesteseeseestdes 5 10 Finding Edge Points Along One Search Contour eee 5 11 Finding Edge Points Along Multiple Search Contours 0 0 0 0 5 12 Finding Points Using Pattern Matching 000 eee eee eseeseeeseceeeeseeeeeseeeenees 5 13 Defining and Creating Good Template Images eee 5 13 Training the Pattern Matching Algorithm o oo eee eeeeeeeeeees 5 15 IMAQ Vision for LabWindows CVI User Manual vi ni com Contents Defining a Search Area csccseesscesnessceesoonsssevecestaveonsseesesesteeoaes 5 16 Setting Matching Parameters and Tolerances eeeeeeeeeeeeees 5 17 Testing the Search Algorithm on Test Images eee 5 18 Using a Ranking Method to Verify Results 0 e
83. inted circuit board PCB being tested may not be placed in the same location with the same orientation The location of the PCB in various images can move and rotate within a known range of values as illustrated in Figure 5 11 Figure 5 11a shows the template used to locate the PCB in the image Figure 5 11b shows an image containing a PCB with a fiducial you want to locate Notice the 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 then you can limit the search for the fiducial to a small region of the image Figure 5 1 1c and Figure 5 11d show examples of a shifted fiducial and a rotated fiducial respectively IMAQ Vision for LabWindows CVI User Manual 5 16 ni com Chapter 5 Performing Machine Vision Tasks Figure 5 11 Selecting a Search Area for Grayscale Pattern Matching 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 parameters Use the imagMatchPattern2 function to set the following elements that influence the IMAQ V
84. ion control part fixture and general environment are key components of the imaging setup All the elements of the image acquisition chain directly affect the accuracy of the measurements National Instruments Corporation 5 1 IMAQ Vision for LabWindows CVI User Manual Chapter 5 3 Performing Machine Vision Tasks Figure 5 1 illustrates the basic steps involved in performing machine vision inspection tasks Locate Objects to Inspect Set Search Areas Find Measurement Points Identify Parts Under Inspection Classify Convert Pixel Coordinates to Real World Coordinates Make Measurements Display Results Figure 5 1 Steps to Performing Machine Vision 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 interested in must always appear inside the ROI you define If the object under inspection is always at the same location and orientation in the images you need to process defining an ROI is simple Refer to the Set Search Areas section of this chapter for information about selecting an ROI Often the object under inspection appears rotated or shifted relative to the reference image in which you located the object When this occurs the ROIs need to shift and
85. ision pattern matching algorithm match mode minimum contrast and rotation angle ranges Match Mode You can set the match mode to control how the pattern matching algorithm handles the template at different orientations If you expect the orientation of valid matches to vary less than 5 from the template set the mode element of the options parameter to IMAQ_ MATCH SHIFT_INVARIANT Otherwise set the mode element to IMAQ_ MATCH _ROTATION_INVARIANT ays Note Shift invariant matching is faster than rotation invariant matching National Instruments Corporation 5 17 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks 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 minContrast element of the imagMatchPattern2 options parameter 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
86. isition and control interfaces A two dimensional 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 images The number of values a pixel can take on which is the number of colors or shades that you can see in the image A window or control that displays an image IMAQ Vision for LabWindows CVI User Manual Glossary image enhancement image file image format image mask image palette image processing image source imaging IMAQ inner gradient inspection inspection function instrument driver intensity 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 is processed if its corresponding mask pixel has a non zero value A source pixel whose correspon
87. l 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 IN ANY APPLICATION INCLUDING THE ABOVE RELIABILITY OF OPERA
88. lter 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 pixel 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
89. ly define an ROI in a window that displays an image Use the tools from the IMAQ Vision tools palette to interactively define and manipulate an ROI National Instruments Corporation 3 1 IMAQ Vision for LabWindows CVI User Manual Chapter 3 Making Grayscale and Color Measurements Table 3 1 describes each of the tools and the manner in which you use them Table 3 1 Tools Palette Functions Icon Tool Name Function Selection Tool Select an ROI in the image and adjust the position of its control N points and contours Action Click the desired ROI or control points Point Select a pixel in the image K Action Click the desired position Line Draw a line in the image 4 Action Click the initial position move the cursor to the final position and click again Rectangle Draw a rectangle or square in the image Action Click one corner and drag to the opposite corner Rotated Rectangle Draw a rotated rectangle in the image v 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 Oval Draw an oval or circle in the image Action Click the center position and drag to the desired size Annulus Draw an annulus in the image G Action Click the center position and drag to the desired size Adjust the inner and outer radii and adjust the start and end angles Broken Line Draw a broken
90. mage 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 pixel A color shape or pattern that you are trying to match in an image using the color matching shape matching or pattern matching functions A template can be a region selected from an image or it can be an entire image Separates objects from the background by assigning all pixels with intensities within a specified range to the object and the rest of the pixels to the background In the resulting binary image objects 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 T
91. 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 Choose the color information carefully when learning color information Specify an image or regions in an image that contain the color or color information that you want to learn Select the level of detail you want the for the learned color information Choose colors that you want to ignore during matching Specifying the Color Information to Learn Because color matching only uses color information to measure similarity the image or regions in the image representing the object must 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 National Instruments Corporation 3 9 IMAQ Vision for LabWindows CVI User Manual Chapter 3 Making Grayscale and Color Measurements 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
92. n 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 is 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 the Attach Calibration Information section of this chapter for more information Then depending on your needs you can do one of the
93. nal Instruments Web site at ni com info and enter the info code feedback 2001 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 susp
94. nce or value plane of a color image into an 8 bit image Note You can also use imaq components of a 64 bit image 3 8 ExtractColorPlanes to process the red green and blue ni com Comparing Colors Chapter 3 Making Grayscale and Color Measurements 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 a reference The color information can consist of a single color or multiple dissimilar colors such as red and blue Use the entire image or regions in the image to learn the color information using imaqgLearnColor which outputs a color spectrum that contains a compact description of the color information in an image or ROI Use the color spectrum to represent the learned color information for all subsequent matching operations Refer to Chapter 14 Color Inspection of the IMAQ Vision Concepts Manual for more information about color learning Define an entire image a region or multiple regions in an image as the inspection or comparison area Use imagMatchColor to compare the learned color information to the color information in the inspection regions This function returns an array of scores that indicates how close the matches are to the learned color information Use the color
95. ness level and the voltage level needed to produce that brightness See gradient filter IMAQ Vision for LabWindows CVI User Manual Glossary 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 histogram inversion histograph IMAQ Vision for LabWindows CVI User Manual G 6 An edge 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
96. nformation that differentiates it from the 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 template image that contains a reference or fiducial pattern 2 Use the reference pattern to train the color pattern matching algorithm with imaqhearnColorPattern 3 Define an image or an area of an image as the search area A small search area reduces the time to find the features 4 Set the featureMode element of the imagMatchColorPattern options parameter to IMAQ_COLOR_AND_SHAPE_FEATURES National Instruments Corporation 5 19 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks 5 Set the tolerances and parameters to specify how the algorithm operates at run time using the options parameter of imaqMatchColorPattern 6 Test the search algorithm on test images using imaqMatchColorPattern 7 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
97. ng an Array to an Image Use imagArrayToImage to convert a 2D array to an image You can also use imaqImageToArray to convert an image to a 2D array Display an Image Display an image in an external window using imagDisplayImage You can display images in 16 different external windows Use the other display functions to configure the appearance of each external window Properties you can set include whether the window has scroll bars a title bar and whether it is resizable You can also use imaqMoveWindow to position the external image window at a particular location on you monitor Refer to the IMAQ Vision for LabWindows CVI Function Reference for a complete list of Display functions 3 Note Image windows are not LabWindows CVI panels They are managed directly by IMAQ Vision You can use a color palette to display grayscale images by applying a color palette to the window Use imaqSetwindowPalette to set 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 0 apply the predefined binary palette For more information about color palettes refer to Chapter 2 Display of the IMAQ Vision Concepts Manual 3 Note At the end of your application close all open external windows using imaqCloseWindow National Instruments Corporation 2 7 IMAQ Vision for LabWindows CVI User Manual Chapter 2 G
98. ng techniques described in the Improve an Image section of this chapter Use imaqhineProfile to get the pixel distribution along a line in the image or use imaqROIProfile to get the pixel distribution along a one dimensional path in the image By looking at the pixel distribution you can determine if the image quality is high 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 input this information into imagEdgeToo12 to find the edges of objects along the line Improve an Image 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 with lookup tables filters grayscale morphology and FFTs National Instruments Corporation 2 9 IMAQ Vision for LabWindows CVI User Manual Chapter 2 Getting Measurement Ready Images Lookup Tables Filters 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
99. nnular region IMAQ Vision does edge detection along search lines that occur 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 LabWindows CVI 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 defined as 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 template image in the form of a reference or fiducial pattern 2 Use the reference pattern to train the pattern matching algorithm with imaqhearnPattern2 3 Define an image or an area of an image as the search area A small search area reduces the time to find the features 4 Set the tolerances and parameters to specify how the algorithm operates at run time using the options parameter of imaqMatchPattern2 5 Test the search algorithm on test images using imaqMat
100. ns in the position of the box Figure 5 12 shows how you can select search areas for different objects 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 IMAQ Vision for LabWindows CVI User Manual 5 22 ni com Chapter 5 Performing Machine Vision Tasks 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 or increasing the template size 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 options parameter of imaqMatchColorPattern to set these elements The following are elements of the IMAQ Vision pattern matching algorithm that influence color pattern matching c
101. of the options parameter To ignore other colors first learn the colors to ignore using imaqLearnColor Then set the colorsToIgnore element of the options parameter to the resulting ColorInformation structure from imaqhearnColor The learning process is time intensive because the algorithm attempts to find unique features of the template that allow for fast accurate matching However you can train the pattern matching algorithm offline and save the template image using imaqWriteVisionFile National Instruments Corporation 5 21 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks 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 if 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 desired pattern lies within the search area For example 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 must be large enough to accommodate these variatio
102. olor 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 LabWindows CVI User Manual G 14 ni com ROI ROI tools rotational shift rotation invariant matching S saturation scale invariant matching segmentation function separation function shift invariant matching skeleton function smoothing filter Sobel filter spatial calibration 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 The amount of white added to a pure color Saturation relates to the richnes
103. olor sensitivity search strategy color score weight ignore background colors minimum contrast and rotation angle ranges These elements are discussed in the following sections Color Sensitivity Use the sensitivity element 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 color sensitivity setting Increase the color sensitivity settings as the color differences decrease Three color sensitivity settings are available in IMAQ Vision IMAQ_SENSITIVITY_LOW IMAQ_SENSITIVITY_MED and IMAQ_SENSITIVITY_HIGH Refer to Chapter 14 Color Inspection of the IMAQ Vision Concepts Manual for more information about color sensitivity Search Strategy Use the strategy element to optimize the speed of the color pattern matching algorithm The search strategy controls the step size sub sampling factor and percentage of color information used from the template National Instruments Corporation 5 23 IMAQ Vision for LabWindows CVI User Manual Chapter 5 3 Performing Machine Vision Tasks Choose from the following search strategies IMAQ_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 sp
104. om 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 A 1 IMAQ Vision for LabWindows CVI User Manual Glossary Numbers 1D 2D 3D AIPD alignment alpha channel area arithmetic operators array auto median 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 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 ty
105. on 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 ared green and blue 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 LabWindows CVI User Manual Glossary connectivity 4 connectivity 8 contrast convex hull convex hull function convolution convolution kernel D Danielsson function determinism digital image dilation driver E edge edge contrast edg
106. our 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 corner elements of the PatternMatch structure to get the position and the bounding rectangle of a match In inspection applications such as optical character verification 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 while a low score indicates a poor match The score can be used as a gauge to determine whether a printed character is acceptable Use the score element of the PatternMatch structure 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 i
107. pe 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 eight bit binary number Also denotes the amount of memory required to store one byte of data IMAQ Vision for LabWindows CVI 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 image 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 a pixel value 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 commonly occurs because the camera is out of focus You can blur an image intentionally by applying a lowpass frequency filter Bitm
108. ponding chapter listed to the side of the item for more information about items in either diagram IMAQ Vision for LabWindows CVI User Manual 1 4 ni com Chapter 1 Introduction to IMAQ Vision a Set Up Your Imaging System Chapter 6 Calibration 1 2 d 2 g S 3 D Q a oO lt Q oy 3 Create an Image y Acquire or Read an Image Chapter 2 Getting Measurement Ready y Images Display an Image Attach Calibration Information y i I I i Analyze an Image I i i i y Improve an Image Make Measurements or Identify Objects in an Image Using Grayscale or Color Measurements and or Particle Analysis and or Machine Vision Figure 1 1 General Steps for Designing a Vision Application 3 Note Diagram items enclosed with dashed lines are optional steps National Instruments Corporation 1 5 IMAQ Vision for LabWindows CVI User Manual Chapter 1 Introduction to IMAQ Vision Define Regions of Interest Chapter 4 Grayscale and Color lt Measurements Measure Measure Wo Grayscale Statistics Color Statistics a y N N Create a Binary Image Locate Objects to Inspect Chapter 5 y Particle lt Improve a Binary Image Set Search Areas Analysis y Find Measurement Points Identify Parts Under Inspection Make Particle Me
109. rast If your image is underexposed or does not have enough 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 or has too much light the majority of your 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 high enough to separate objects of interest from the background IMAQ Vision for LabWindows CVI User Manual 2 8 ni com Chapter 2 Getting Measurement Ready Images 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 including 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 processi
110. ration vij IMAQ Vision for LabWindows CVI User Manual Contents Appendix A Technical Support and Professional Services Glossary Index IMAQ Vision for LabWindows CVI User Manual viii ni com About This Manual Conventions The IMAQ Vision for LabWindows CVI User Manual is intended for engineers and scientists who have knowledge of the LabWindows CVI programming environment and need to create machine vision and image processing applications using C functions The manual guides you through tasks beginning with setting up your imaging system to taking measurements Y 3 bold italic monospace The following conventions are used 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 character
111. rection twice IMAQ_ MT _NORM_MOMENT_OF_INERTIA_XY Normalized moment of inertia in the x and y directions IMAQ_ MT _NORM_MOMENT_OF_INERTIA_YY Normalized moment of inertia in the y direction twice IMAQ Vision for LabWindows CVI User Manual 4 8 ni com Chapter 4 Performing Particle Analysis Table 4 1 Particle Measurements Continued Measurement Description IMAQ_ MT _NORM_MOMENT_OF_INERTIA_XXX Normalized moment of inertia in the x direction three times IMAQ_MT_NORM_MOMENT_OF_INERTIA_XXY Normalized moment of inertia in the x direction twice and the y direction once IMAQ_MT_NORM_MOMENT_OF_INERTIA_XYY Normalized moment of inertia in the x direction once and the y direction twice IMAQ_MT_NORM_MOMENT_OF_INERTIA_YYY Normalized moment of inertia in the y direction three times IMAQ_MT_NUMBER_OF_HOLES Number of holes in the particle IMAQ_MT_NUMBER_OF_HORIZ_SEGMENTS Number of horizontal segments in the particle IMAQ_MT_NUMBER_OF_VERT_SEGMENT S Number of vertical segments in the particle IMAQ_MT_ORIENTATION Angle of the line that passes through the particle center of mass about which the particle has the lowest moment of inertia IMAQ_MT_PERIMETER Length of the outer boundary of the particle IMAQ MT PARTICLE _AND_HOLES_AREA Area of a particl
112. reshold is an 8 bit binary image Improve the Binary Image 3 After you threshold your image you may want to improve the resulting binary image with binary morphology You can use primary binary 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 opposed to 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 The advanced morphology functions require that you specify the type of connectivity to use 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 Note Use the same type of connectivity throughout your application IMAQ Vision for LabWindows CVI User Manual 4 2 ni com Chapter 4 Performing Particle Analysis Removing Unwanted Particles Use imagRejectBorder to remove particles that touch the border of th
113. restsresreresresresenenes 5 31 Display Result v sc scssezsot eats sesessigctens a E EE a E E E E ates EA RS 5 31 Chapter 6 Calibrating Images Perspective and Nonlinear Distortion Calibration sssesesseseseesesresesrsresreersresreeesereses 6 1 Defining a Calibration Template cece eececseeeseeeeeeceaeeeeeseseeeeaeenaes 6 2 Defining a Reference Coordinate System 0 c ccc eceeeeseees esses tseeeeeeeseeeeeees 6 3 Learning Calibration Information eee ec eeeeseeeeeeseeneceeeessenseeaeseeeeaeenaes 6 5 Specifying Scaling Factors eee eseeseeseeeseeseceseessceeeeeeeeeeseeeeees 6 6 Choosing a Region of Interest eee eeeeseeseereeeeeeseeeeeeseteeeeaees 6 6 Choosing a Learning Al gorithm 00 eee eee ese eeseeeeneeeseteeenseteees 6 6 Using the Learning Score eee eee eseeeeeesecseeeseceeeeseceeeaeeeeeeseenaes 6 7 Learning the Error Map d ctees ais cident edie aes 6 8 Learning the Correction Table eee ec eeeeceeseceeeneeeseeeeneeeseenees 6 8 Setting the Scaling Method 00 eee eeecereceeeeseseeeeseeseeeaeeeees 6 8 Calibration Invalidation 0 eee eee eseseeeeseeseeeseceeeeseeeeesesneeeseesees 6 8 Simple Caltbratwonss secs ccsssevethavees deck cect teed leben cogensutteiees tevees inves EA T O EET 6 9 Save Calibration Information eee eececeseeeeeesecseeeseesseesecseeeseesseesseeseeseseaeseeeaees 6 10 Attach Calibration Information enee aeanoea eE EEEN EEE IAS TREES EEI SENS 6 10 National Instruments Corpo
114. rizontal angle of a line region National Instruments Corporation Figure 3 3 Tools Palette Tools and Information 3 5 IMAQ Vision for LabWindows CVI User Manual Chapter 3 Making Grayscale and Color Measurements The following list describes how you can display the tools palette in a separate window and manipulate the palette e Use imaqgShowToolWindow to display the tools palette in a floating window e Use imagSetupToolWindow to configure the appearance of the tools palette e Use imagMoveToolWindow to move the tools palette e Use imaqcloseToolWindow to close the tools palette If you want to draw an ROI without using an ROI constructor or displaying the tools palette in a separate window use imaqSetCurrentTool This function allows you to select a contour from the tools palette without opening the palette Defining Regions Programmatically When you have an automated application you may need to define regions of interest programmatically To programmatically define an ROI create the ROI using imaqCcreateROI and then add the individual contours A contour is a shape that defines an ROI You can create contours from points lines rectangles ovals polygons and annuli For example to add a rectangular contour to an ROI use imagAddRectContour Specify regions by providing basic parameters that describe the region you want to define For example define a point by providing the x coordinate
115. rotate with the parts of the object in which you are interested To move the ROIs with the object you must 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 IMAQ Vision for LabWindows CVI User Manual 5 2 ni com Chapter 5 Performing Machine Vision Tasks it appears shifted and rotated in the image you need to process This coordinate system is referred to as the measurement coordinate system The measurement methods automatically move the ROIs to the correct position using the position of the measurement coordinate system with respect 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 transform using edge detection or pattern matching The output of the edge detection and pattern matching functions that build a coordinate system are the origin angle and axes direction of the coordinate system Some machine vision functions take this output and adjust the regions of inspection automatically You can also use these outputs to programmatically move the regions of inspection relative to the object National Instruments Corporation 5 3 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks Using Edge Detection to Build a Coordinate Transform You can build a coor
116. s 5 13 testing search algorithm 5 18 5 25 thresholding images 4 1 tolerances defining for pattern matching 5 17 setting for pattern matching 5 23 tools palette closing 3 6 configuring 3 6 displaying 3 6 moving 3 6 Tools palette functions 3 2 training color pattern matching algorithm 5 21 pattern matching algorithm 5 15 training and certification NI resources A 1 troubleshooting NI resources A 1 truncation highpass 2 13 lowpass 2 13 U using learning scores 6 7 simple calibration 6 9 V Vision applications creating 1 4 W Web resources A 1 windows displaying images in external windows 2 7 ni com
117. s learning color distribution 3 11 ni com National Instruments support and services A 1 NI Vision Assistant x NI Vision Builder for Automated Inspection x NI IMAQ xi Nth order filter 2 11 0 objects 5 2 inspecting 5 2 locating 5 2 open operation 4 3 opening particles 4 3 P particle analysis performing 4 1 particles 4 1 analyzing 4 1 closing 4 4 counting 4 4 eroding 4 3 filling holes 4 3 measuring 4 4 opening 4 3 removing unwanted particles 4 3 separating touching particles 4 3 smoothing boundaries 4 3 parts identifying 5 28 pattern matching color score weight 5 24 defining tolerances 5 17 interpreting results 5 19 minimum contrast 5 18 5 24 mode 5 17 orientation 5 17 selecting search strategies 5 23 training color pattern matching algorithm 5 21 National Instruments Corporation l 5 Index training the pattern matching algorithm 5 15 using color pattern matching 5 19 PDF417 barcodes reading 5 31 performing machine vision inspection tasks 5 1 particle analysis 4 1 pixel coordinates converting to real world coordinates 5 26 points finding using color location 5 25 processing components of color images 3 7 programming examples NI resources A 1 R reading 1D barcodes 5 30 characters 5 29 data matrix barcodes 5 30 images 2 5 images from file 2 6 PDF417 barcodes 5 31 reference coordinate systems defining 6 3 regions of interest ROIs
118. s 4 Circle Fit To Edge Points Figure 5 6 Finding a Circular Feature Use imaqFindEdge and imaqFindConcentricEdge to locate the intersection points between a set of search lines within the search region and the edge of an object You can specify the search region using imaqSelectRect or imaqSelectAnnulus Specify the separation between the lines that the functions use to detect edges The functions 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 functions return the coordinates of the edges found Finding Edge Points Along One Search Contour Use imagSimpleEdge or imaqEdgeToo12 to find edge points along a contour Using imaqgSimpleEdge you can find the first edge last edge or all edges along the contour Use imagSimpleEdge when your image contains little noise and the object and background are clearly differentiated Otherwise use imaqEdgeTool2 National Instruments Corporation 5 11 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks These functions require you to input the coordinates of the points along the search contour Use imaqROIProfile to obtain the coordinates along the edge of each contour in an ROL If you have a straight line use imagGet PointsOnLine to obtain the points along the line inste
119. s after you set regions of inspection you can also identify parts using classification optical character recognition OCR and barcode reading Classifying Samples 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 e Sorting Sorts objects of varied shapes For example sorting different mechanical parts on a conveyor belt into different bins e 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 Classification Training to launch the NI Classification Training Interface After you have trained samples of the objects you want to classify use the following functions to classify the objects 1 Use imaqReadClassifierFile toread ina classifier session that you created using the NI Classification Training Interface 2 Use imagClassify 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 3 Use imaqDispose to free the resources that the classifi
120. s 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 object Separates objects that touch each other by narrow isthmuses A pattern matching technique in which the reference pattern can be located anywhere 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 Assigns physical dimensions to the area of a pixel in an image IMAQ Vision for LabWindows CVI User Manual Glossary 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 LabWindows CVI User Manual 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 i
121. s 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 National Instruments Corporation ix IMAQ Vision for LabWindows CVI 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 LabWindows CVI Function Reference If you need information about IMAQ Vision functions while creating your application refer to this help file 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 If 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
122. sion for LabWindows CVI User Manual 1 2 ni com Chapter 1 Introduction to IMAQ Vision Table 1 1 IMAQ Vision Function Types Continued Function Type Description Caliper Functions designed for gauging measurement and inspection applications Operators Functions that perform arithmetic logic and comparison operations with two images or with an image and a constant value Analytic Functions that perform basic geometric calculations on an image Geometry Frequency Functions for the extraction and manipulation of complex planes Functions Domain of this type perform Fast Fourier Transform FFT inverse FFT truncation Analysis attenuation addition subtraction multiplication and division of complex images Barcode I O Functions that find and read barcodes LCD Functions that find and read seven segment LCD characters Meter Functions that return the arc information of a meter and read the meter Utilities Functions that return structures and a function that returns a pointer to predefined convolution matrices OCR Functions that perform optical character recognition on an image Classification Functions that classify an image or feature vector Obsolete Functions that are no longer necessary but may exist in older applications IMAQ Machine Vision Function Tree The IMAQ Machine Vision function tree NIMachineVision fp contains separate classes corresponding to
123. ss filter with imagConvolve or imagNthOrderFilter 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 imaqconvolve or imagNthOrderFilter or you can use a predefined highpass filter with imaqEdgeFilter or imaqCannyEdgeFilter The imagEdgeFilter function allows you to find edges in an image using predefined edge detection kernels such as the Sobel Prewitt and Roberts kernels IMAQ Vision for LabWindows CVI User Manual 2 10 ni com Chapter 2 Getting Measurement Ready Images Convolution Filter The imaqConvolve function allows you to use a predefined set of lowpass and highpass filters Each filter is defined by a kernel of coefficients Use imaqGetKernel to retrieve predefined kernels If the predefined kernels do not meet your needs define your own custom filter using a 2D array of floating point numbers Nth Order Filter The imagNthOrderFilter function allows you to define 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 Use imagMedianFilter to apply a median filter For more information about Nth order filters refer to Chapter 5 Image Processing of the IMAQ Vision Concepts Manual Grayscale Morphology Perform grayscale
124. t 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 LabWindows CVI 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 For information about acquiring images refer to the Acquire or Read an Image section of Chapter 2 Getting Measurement Ready 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 into imaqLearnCalibrationGrid 3 Note Ifyou want to specify a list of points instead of a grid use imaqLearnCalibrationPoints to learn the calibration information Use the CalibrationPoints structure to specify the pixel to real world mapping National Instruments Corporation 6 5 IMAQ Vision for LabWindows CVI User Manual Chapter 6 Calibrating Images Specifying Scaling Factors
125. tative analysis functions You can obtain the center of energy for an image with the centroid function Use imaqLightMeterPoint to measure the light intensity at a point in the image Use imagLightMeterLine to get pixel value statistics along a line in the image such as mean intensity standard deviation minimum intensity and maximum intensity Use imaqLightMeterRect to get the pixel value statistics within a rectangular region in an image Use imaqQuantify 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 image mask has a unique intensity value Use imaqLabe12 to label your image mask Use imaqCentroid 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 images However you can analyze and process individual components of a color image Using imagExtractColorPlanes 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
126. te 2 Define a rectangular ROI in which you expect to find the template Use the options parameter to select your options for finding the pattern and the results that you want to overlay onto the image When setting the Mode element select IMAQ_MATCH_ROTATION_INVARIANT when you expect your template to appear rotated in the inspection images Otherwise select IMAQ_MATCH_SHIFT_INVARIANT Set the options parameter to NULL to use the default options 4 Choose the mode for the function To build a coordinate transform for the first time set the mode parameter to IMAQ_FIND_REFERENCE To update the coordinate system in subsequent images set the mode parameter to IMAQ_UPDATE_TRANSFORM IMAQ Vision for LabWindows CVI User Manual 5 6 ni com Chapter 5 Performing Machine Vision Tasks Choosing a Method to Build the Coordinate Transform Figure 5 4 guides you through choosing the best method for building a coordinate transform for your application Object positioning accuracy better than 65 degrees The object under The object contains a search area Yes inspection has a straight distinct edge main axis second distinct edge not parallel to the main axis in the same No 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
127. tern matching 5 19 frequency domains converting images 2 12 function tree IMAQ Machine Vision 1 3 IMAQ Vision 1 2 function types table IMAQ Machine Vision 1 3 IMAQ Vision 1 2 G getting center of energy for an image 3 7 image statistics 3 7 grayscale morphology 2 11 grayscale statistics measuring 3 7 National Instruments Corporation l 3 Index H help technical support A 1 highpass attenuation 2 13 filters 2 10 truncation 2 13 holes filling in particles 4 3 l identifying parts 5 28 ignoring learned colors 3 13 image masks defining 3 6 image quality 2 8 images acquiring 2 5 analyzing 2 8 analyzing components 3 7 applying LUTs 2 10 attaching calibration information 2 8 calibrating 6 1 comparing color content 3 9 computing the energy center 3 7 computing the energy center of an ROI in an image 3 7 converting 2D arrays to images 2 5 2 7 creating 2 2 creating binary images 4 1 defining template images 5 13 destination 2 4 detecting edges 5 9 displaying 2 7 extracting planes 3 8 filtering 2 10 filtering grayscale features 2 11 finding features 5 13 getting statistics 3 7 getting the center of energy 3 7 ignoring learned colors 3 13 improving 2 9 IMAQ Vision for LabWindows CVI User Manual Index improving binary images 4 2 improving sharpness of transitions 2 10 inspecting 2 8 learning color information 3 9 learning the color distrib
128. the leftmost particle point and the x coordinate of the rightmost particle point IMAQ_MT_BOUNDING_RECT_DIAGONAL Distance between opposite corners of the bounding rectangle IMAQ_MT_CENTER_OF_MASS_X X coordinate of the point representing the average position of the total particle mass assuming every point in the particle has a constant density IMAQ_MT_CENT ER_OF_MASS_Y Y coordinate of the point representing the average position of the total particle mass assuming every point in the particle has a constant density IMAQ_MT_COMPACTNI ESS FACTOR Area divided by the product of bounding rectangle width and bounding rectangle height IMAQ_MT_CONVEX_HULL_AREA Area of the smallest convex polygon containing all points in the particle IMAQ_MT_CONVEX_HULL_PERIMETER Perimeter of the smallest convex polygon containing all points in the particle National Instruments Corporation 4 5 IMAQ Vision for LabWindows CVI User Manual Chapter 4 Performing Particle Analysis Table 4 1 Particle Measurements Continued Measurement Description IMAQ_MT_EQUIVALENT_ELLIPSE_MAJOR_AXIS Length of the major axis of the ellipse with the same perimeter and area as the particle IMAQ_MT_EQUIVALENT_ELLIPSE_MINOR_AXIS Length of the minor axis of the ellipse with the same perimeter and area as the particle IMAQ_MT_EQU
129. ticle Analysis Table 4 1 Particle Measurements Continued Measurement Description IMAQ_MT_MAX FERET_DIAMETER_START_Y Y coordinate of the start of the line segment connecting the two perimeter points that are the furthest apart IMAQ_MT_MAX HORIZ_SEGMENT_LENGTH_LEFT X coordinate of the leftmost pixel in the longest row of contiguous pixels in the particle IMAQ_MT_MAX HORIZ_SEGMENT_LENGTH_RIGHT X coordinate of the rightmost pixel in the longest row of contiguous pixels in the particle IMAQ_MT_MAX HORIZ_SEGMENT_LENGTH_ROW Y coordinate of all of the pixels in the longest row of contiguous pixels in the particle IMAQ_ MT_MOMENT_OF_INERTIA_XX Moment of inertia in the x direction twice IMAQ_MT_MOMENT_OF_INERTIA_XY Moment of inertia in the x and y directions IMAQ_MT_MOMENT_OF_INERTIA_YY Moment of inertia in the y direction twice IMAQ_MT_MOMENT_OF_INERTIA_XXX Moment of inertia in the x direction three times IMAQ_MT_MOMENT_OF_INERTIA_XXY Moment of inertia in the x direction twice and the y direction once IMAQ_MT_MOMENT_OF_INERTIA_XYY Moment of inertia in the x direction once and the y direction twice IMAQ_MT_MOMENT_OF_INERTIA_YYY Moment of inertia in the y direction three times IMAQ_ MT _NORM_MOMENT_OF_INERTIA_XX Normalized moment of inertia in the x di
130. tion are available for you to use Select an ROI tool from the tools palette Draw an ROI on your image Resize or reposition the ROI until it specifies the area you want to process Click OK to output a description of the ROI You can use this description as an input for the following functions ROI Selection Function Measurement Function imaqSelectRect imaqFindPattern imaqClampMax imaqClampMin imagFindEdge imaqSelectAnnulus imaqFindCircularEdge imaqFindConcentricEdge IMAQ Vision for LabWindows CVI User Manual 5 8 ni com Chapter 5 Performing Machine Vision Tasks Defining Regions Programmatically When you have an automated application you need to define ROIs programmatically You can programmatically define regions in two ways e Specify the contours of the ROI e Specify individual structures by providing basic parameters that describe the region you want to define You can specify a rotated rectangle by providing the coordinates of the center the width the height 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 3 Making Grayscale and Color Measurements for more information about defining ROIs
131. tion grid The software rotates and scales a pixel coordinate according to predefined coordinate reference and scaling factors You can assign the calibration to an arbitrary image using imaqSetSimpleCalibration To perform a simple calibration set a coordinate reference 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 Use the system parameter to define the coordinate system Use the grid parameter to specify the scaling factors Use the method parameter to set the scaling method Set the learnTable parameter to TRUE to learn the correction table 1 Origin Figure 6 7 Defining a Simple Calibration National Instruments Corporation 6 9 IMAQ Vision for LabWindows CVI User Manual Chapter 6 Calibrating Images Save Calibration Information After you learn the calibration information you can save it so that you do not have to relearn the information for subsequent processing Use imaqwriteVisionFile to save the image of the grid and its associated calibration information to a file To read the file containing the calibration information use
132. tion 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 sub pixel accuracy 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 imaqhearnColorPattern 3 Define an image or an area of an image as the search area A small search area reduces the time to find the features 4 Set the featureMode element of the imagMatchColorPattern options parameter to IMAQ_COLOR_FEATURES 5 Set the tolerances and parameters to specify how the algorithm operates at run time using the options parameter of imaqMatchColorPattern National Instruments Corporation 5 25 IMAQ Vision for LabWindows CVI User Manual Chapter 5 Performing Machine Vision Tasks 6 Test the color location algorithm on test images using imaqMatchColorPattern 7 Verify the results using a ranking method You can save the template image using imaqwWriteVisionFile Convert Pixel Coordinates to Real World Coordinates
133. type as shown in Figure 3 7 Figure 3 7 Using the Entire Image to Learn Color Distribution 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 IMAQ Vision for LabWindows CVI User Manual 3 10 ni com Chapter 3 Making Grayscale and Color Measurements Figure 3 8 Using a Single Region to Learn Color Distribution Using Multiple Regions in the Image The interaction of light with the 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 around the 3 amp fuse in the upper row and then do a color matching for the 3 amp fuse in the upper row
134. uire only certain images supply imaqgSetupSequence with a table describing the number of frames to skip after each acquired frame Acquire images continually through a ringed buffer acquisition Set up the acquisition using imaqSetupRing Use imagStartAcquisition to start acquiring images into the acquired ring buffer To get an image from the ring call imagExtractFromRing or imaqCopyRing Use imaqStopAcquisition to stop the acquisition 3 Note You must use imgClose to release resources associated with the image acquisition device Reading a File Use imagReadFile to open and read data from a file stored on your computer into the image reference You can read from image files stored in several standard formats BMP TIFF JPEG PNG and AIPD The software automatically converts the pixels it reads into the type of image you pass in IMAQ Vision for LabWindows CVI User Manual 2 6 ni com Chapter 2 Getting Measurement Ready Images Use imaqReadVisionFile to open an image file containing additional information such as calibration information template information for pattern matching or overlay information For more information about pattern matching templates and overlays refer to Chapter 5 Performing Machine Vision Tasks You can also use imagGetFileInfo to retrieve image properties such as image size recommended image type and calibration units without actually reading all the image data Converti
135. um features of the template for the particular matching process 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 can also save time by training the pattern matching algorithm offline and then saving the template image with imaqgWriteVisionFile Defining a Search Area Two equally important factors define the success of a pattern matching algorithm 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 task the presence of additional instances of the pattern can produce incorrect results To avoid this reduce the search area so that only the desired 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 or increasing the template size 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 pr
136. ut you can set the object pixels to 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 imagThreshold to threshold your image National Instruments Corporation 4 1 IMAQ Vision for LabWindows CVI User Manual Chapter 4 Performing Particle Analysis If all the objects in your grayscale image are either brighter or darker than your background you can use imaqAutoThreshold to automatically determine the optimal threshold range and threshold your image 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 more independent of changes in the overall brightness and contrast of the image than a fixed threshold These techniques are more resistant to changes in lighting which makes them well suited for automated inspection tasks If your grayscale image contains objects that have multiple discontinuous grayscale values use imagMultithreshold to specify multiple threshold ranges If you need to threshold a color image use imagColorThreshold You must specify threshold ranges for each of the color planes using either the RGB or HSL color model The binary image resulting from a color th
137. ution 3 10 loading from file 2 5 measuring light intensity 3 7 modifying complex images 2 13 processing components 3 7 reading 2 5 reading from file 2 6 setting color sensitivity 5 23 source 2 4 taking color measurements 3 1 taking grayscale measurements 3 1 thresholding 4 1 imaging systems calibrating 2 2 setting up 2 1 IMAQ Machine Vision function tree 1 3 function types table 1 3 IMAQ Vision function tree 1 2 function types table 1 2 improving binary images 4 2 images 2 9 sharpness of transitions 2 10 inspecting images 2 8 objects 5 2 inspection tasks performing 5 1 instrument drivers xi NI resources A 1 interpreting pattern matching results 5 19 invalidating calibrations 6 8 IMAQ Vision for LabWindows CVI User Manual K KnowledgeBase A 1 L learning calibration information 6 5 color information 3 9 color spectrum 3 10 correction tables 6 8 error maps 6 8 learning algorithms choosing 6 6 learning scores using 6 7 light intensity measuring in images 3 7 locating 5 2 measurement points 5 9 lowpass attenuation 2 12 filters 2 10 truncation 2 13 LUTs 2 10 machine vision tasks 5 1 measurement points locating 5 9 measurements analytic geometry 5 27 distance measurements 5 26 instrument reader 5 27 measuring grayscale statistics 3 7 light intensity in images 3 7 particles 4 4 modifying complex images 2 13 moving tools palette 3 6 multiple ROI
138. ution 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 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 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 Windows Sun Product IMAQ Vision for LabWindows CVI User Manual Glossary line gauge line profile linear filter logarithmic function logic operators lossless compression lossy compression lowpass attenuation lowpass FFT filter lowpass fi
139. uts IMAQ Vision resizes the destination image to hold the result if the destination is not the appropriate size The following examples illustrate source and destination images with imaqTranspose imaqTranspose myImage myImage This function creates a transposed image using the same image for the source and destination The contents of myImage change imaqTranspose myTransposedImage myImage This function creates a transposed image and stores it in a destination different from the source The myImage image remains unchanged and myTransposedImage contains the result Functions that perform arithmetic or logical operations between two images have two source images and a destination image You can perform an operation between two images and then either store the result in a separate destination image or in one of the two source images In the latter case make sure you no longer need the original data in the source image before storing the result over the data The following examples show the possible combinations using imaqAdd imaqAdd myResultImage myImageA myImageB This function adds two source images my ImageA and my ImageB and stores the result in a third image myResultImage Both source images remain intact after processing IMAQ Vision for LabWindows CVI User Manual 2 4 ni com Chapter 2 Getting Measurement Ready Images imaqAdd myImageA myImageA myImageB This function adds two source
140. with NI 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 If 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 LabWindows CVI User Manual X ni com About This Manual Other Documentation e Your National Instruments image acquisition IMAQ device user manual TIf you need installation instructions and device specific information refer to your device user manual e Getting Started With Your IMAQ System 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 TIf 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
141. you get a very high match score close to 1000 But the match score for the 3 amp fuse in the lower row is quite low 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 3 amp fuse in the upper row hold down the lt Shift gt key and draw another ROI around the 3 amp fuse in the lower row The new color spectrum represents 3 amp fuses better and results in high match scores around 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 National Instruments Corporation 3 11 IMAQ Vision for LabWindows CVI User Manual Chapter 3 Making Grayscale and Color Measurements 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 anot
142. ystems using edge detection 5 4 coordinate systems using pattern matching 5 6 image masks 3 6 IMAQ Vision for LabWindows CVI User Manual l 2 pattern matching tolerances 5 17 reference coordinate systems 6 3 regions of interest 3 1 ROIs 6 6 ROIs interactively 3 1 5 8 ROIs programmatically 3 6 5 9 search areas 5 8 5 16 5 22 template images 5 13 deployment application xi destination images 2 4 detecting circular edges 5 10 edges 5 9 edges along a contour 5 11 edges along multiple contours 5 12 rectangular edges 5 10 determining 2 8 image quality 2 8 diagnostic tools NI resources A 1 displaying images 2 7 results 5 31 tools palette 3 6 documentation conventions used in manual ix NI resources A 1 related documentation x drivers NI resources A 1 NI IMAQ xi E edge detection 5 9 edges detecting 5 9 detecting along a contour 5 11 detecting along multiple contours 5 12 detecting circular edges 5 10 eroding particles 4 3 erosion 4 3 ni com error maps learning 6 8 examples NI resources A 1 external windows displaying images 2 7 extracting planes of color images 3 8 F Fast Fourier Transform 2 12 features finding in images 5 13 FFT 2 12 filtering grayscale features of an image 2 11 images 2 10 filters convolution 2 11 highpass 2 10 lowpass 2 10 Nth order 2 11 finding image features 5 13 points using color location 5 25 points using color pat

National Instruments IMAQ Vision for LabWindows TM /CVI User's Manual

Contents

Download Pdf Manuals

Related Search

Related Contents