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automated iris recognition system using cmos camera with proximity

1. Infineon technologies OSRAM 116 SFH 484 SFH 485 Kennwerte 7 25 C Characteristics Bezeichnung Symbol Wert Einheit Parameter Symbol Value Unit Temperaturkoeffizient von I bzw TC 0 5 Ig 100 mA Temperature coefficient of I or Ip 100 mA Temperaturkoeffizient von Ip 100 mA 2 mV K Temperature coefficient of Jc 100 mA Temperaturkoeffizient von J 100 mA TC 0 25 nm K Temperature coefficient of Ip 100 mA Gruppierung der Strahlstarke Achsrichtung gemessen bei einem Raumwinkel 0 001 sr bei SFH 484 bzw 0 01 sr bei SFH 485 Grouping of Radiant Intensity I in Axial Direction at a solid angle of Q 0 001 sr at SFH 484 or Q 0 01 sr at SFH 485 Bezeichnung Symbol Wert Einheit Parameter Value Unit SFH SFH SFH SFH SFH 484 484 1 484 2 485 485 2 Strahlst rke Radiant intensity Ls 50 50 gt 80 16 gt 25 mW sr I 100 mA t 20 ms max 160 100 80 mW sr Strahlst rke Radiant intensity Ip 1 f 100 us Lis 800 700 900 300 340 mW sr 2000 01 01 4 OPTO SEMICONDUCTORS Infineon technologies OSRAM 117 TFDU5102 Vishay Telefunken Ordering Information Hart Number Qty Reel Description TFDU5102 TR3 1000 pcs Oriented in carrier tape for side view surface mounting TFDU5102 TT3 1000 pcs Oriented in carrier tape for top vie
2. SD High 85 C Mode Floating Not Ambient Light Sensitive Operating Temperature Range Output Voltage Low Rioad 2 2 V Cioad 15 pF Output Voltage High Rioad 2 2 V Cioad 15 pF Input Voltage Low V Txd SD Mode Mode Input Voltage High CMOS level V Txd SD Mode Mode level Vcc gt 4 5 V V Input Leakage Current uA Txd SD Mode Input Leakage Current uA Mode Input Capacitance pF WU Standard Illuminant typical threshold level is between 0 5 x Vcc Vcc 3 V and 0 4 x Veg Veg 5 5 V It is recommended to use the specified min max values to avoid increased operating current www vishay com Document Number 82535 4 11 Rev A1 0 13 Oct 00 120 TFDU5102 Vishay Telefunken Optoelectronic Characteristics Tamb 25 Vcc 3 0 V to 5 25 V unless otherwise noted Typical values are for DESIGN AID ONLY not guaranteed nor subject to production testing Parameters Test Conditions Symbol Min Typ Max Unit Receiver Minimum Detection TFDU5102 Es 25 40 mW m Threshold Irradiance 9 6 kbit s to 115 2 kbit s SIR Mode 7 850 nm to 900 nm Minimum Detection TFDU5102 Ee 65 95 mW m Threshold Irradiance 1 152 Mbit s MIR Mode A 850 nm to 900 nm Maximum Detection 7 850 nm to 900 nm ES 5 10 kW m Threshold Irradiance Logic LOW Receiver Es 4 mW m Input Irradiance Rise Time of Output 10 to 90 02 2 kQ 15
3. Thermal Overload Protection TO 220 D PAK package and with several fixed output Short Circuit Protection voltages making them useful in a wide range of Output Transistor Safe Operating Area Protection applications Each type employs internal current limiting thermal shut down and safe operating area protection making it essentially indestructible If adequate heat sinking is provided they can deliver over 1 output current Although designed primarily as fixed voltage regulators these devices can be used with external components to obtain adjustable voltages and currents TO 220 1 Input 2 GND 3 Output Internal Block Digram SERIES PASS ELEMENT SOA PROTECTION AMPLIFIER INPUT OUTPUT CURRENT GENERATOR REFERENCE VOLTAGE STARTING CIRCUIT PROTECTION GND Rev 1 0 1 2001 Fairchild Semiconductor Corporation 122 MC78XX LM78XX MC78XXA Absolute Maximum Ratings Weg ee Ces Input Voltage for Vo 5V to 18V Vi 35 for Vo 24V Vi 40 Thermal Resistance Junction Cases TO 220 a Thermal Resistance Junction Air 220 R a 65 Tom Operating Temperature Range 0 4125 Storage Temperature Range 65 150 Electrical Characteristics MC7805 LM7805 Refer to test circuit 0 lt Ty lt 125 C lo 500mA Vi 10V Ci 0 33 Co 0 1uF unless otherwise specified Parameter Dn MC7805 LM7805 cf KR Vo O
4. T2 lower threshold value Returns bw the thresholded image containing values 0 or 1 Function performs hysteresis thresholding of an image All pixels with values above threshold T1 are marked as edges All pixels that are adjacent to points that have been marked as edges and with values above threshold T2 are also marked as edges Eight connectivity is used It is assumed that the input image is non negative function bw hysthresh im T1 T2 if 2 gt T1 T2 lt 0 T1 lt 0 Check thesholds are sensible 1 must be gt T2 and both must be gt 0 90 end rows cols size im Precompute some values for speed convenience rc rows cols rcmr rc rows rows 1 bw im Make image into a column vector pix find bw gt 1 Find indices of all pixels with value gt T1 npix size pix 1 Find the number of pixels with value gt T1 stack zeros rows cols 1 Create a stack array that should never overflow stack 1 npix pix Put all the edge points on the stack stp npix set stack pointer for k 1 npix bw pix k 1 mark points as edges end Precompute an array O of index offset values that correspond to the eight surrounding pixels of any point Note that the image was transformed into a column vector so if we reshape the image back to a square the indices surrounding a pixel with ind
5. POSSE SHSSSO SEH SH SH SESH SOHO SOE HOH ELLE E nonmaxsup m NONMAXSUP Usage im nonmaxsup inimage orient radius Function for performing non maxima suppression on an image using an orientation image It is assumed that the orientation image gives feature normal orientation angles in degrees 0 180 input 9o image be non maxima suppressed orient image containing feature normal orientation angles in degrees 0 180 angles positive anti clockwise radius distance in pixel units to be looked at on each side of each pixel when determining whether it is a local maxima or not Suggested value about 1 2 1 5 Note This function is slow 1 2 mins to process a 256x256 image It uses bilinear interpolation to estimate intensity values at ideal real valued pixel locations on each side of pixels to determine if they are local maxima function im nonmaxsup inimage orient radius if size inimage size orient error image and orientation image are of different sizes end 87 if radius lt 1 error radius must be gt 1 end rows cols size inimage im zeros rows cols Preallocate memory for output image for speed iradius ceil radius Precalculate x and y offsets relative to centre pixel for each orientation angle angle 0 180 pi 180 Array of angles 1 degree increments but in radians xoff
6. iru imgsize 1 end if icu gt imgsize 2 icu imgsize 2 end to find the inner pupil use just the region within the previously detected iris boundary imagepupil eyeimage irl iru icl icu find pupil boundary rowp colp findcircle imagepupil Ipupilradius upupilradius 0 6 2 0 25 0 25 1 00 1 00 rowp double rowp colp double colp r double r 85 row double irl rowp col double icl colp row round row col round col circlepupil row col r set up array for recording noise regions noise pixels will have NaN values imagewithnoise double eyeimage find top eyelid topeyelid imagepupil 1 rowp r lines findline topeyelid if size lines 1 gt 0 xl yl linecoords lines size topeyelid yl double yl irl 1 xl double xl icl 1 yla max yl y2 1 yla sub2ind size eyeimage yl xl imagewithnoise ind3 NaN imagewithnoise y2 xl NaN end find bottom eyelid bottomeyelid imagepupil rowp r size imagepupil 1 lines findline bottomeyelid if size lines 1 gt 0 xl yl linecoords lines size bottomeyelid yl double yl irl rowp r 2 xl double xl icl 1 yla min yl y2 yla size eyeimage 1 86 ind4 sub2ind size eyeimage yl xl imagewithnoise ind4 NaN imagewithnoise y2 xl NaN end ref eyeimage lt 100 coords find ref 1 imagewithnoise coords NaN
7. disp Arduino is not connected please re create the object before using this function errstr Arduino not connected return end make sure is valid if isvalid ser 75 disp Serial connection invalid please recreate the object to reconnect to a serial port errstr Serial connection invalid return end case open check openness if strcmpi get ser Status open disp Serial connection not opened please recreate the object to reconnect to a serial port errstr Serial connection not opened return end otherwise complain error second argument must be either valid or open end end 96 chackser end static methods end class def 99999999999 99 9 9 999999999 99 99 9999999 999999999 9 9 9999999 9 9 99 99999 99 99 99 irisrecognition m function varargout irisrecognition varargin Begin initialization code DO NOT EDIT gui Singleton 1 gui State struct gui Name mfilename gui Singleton gui Singleton Out OpeningFcn Girisrecognition OpeningFon gui OutputFcn irisrecognition_OutputFcn out LayoutFcn ou Callback if nargin amp amp ischar varargin 1 76 gui_State gui_Callback str2func varargin 1 end if nargout varargout 1 nargout gui_mainfcn gui_State varargin else gui_mainfcn gui_State varargin end End initialization code DO NOT EDIT Executes just before untitled is made v
8. distribution and n is the total number of samples The Equal Error Rate EER compares the accuracy of devices The lower the EER the more accurate the system is considered to be The characteristic of the wavelet transform are the concept used in encoding iris bit patterns These metrics are useful in achieving the accuracy and efficiency of wavelet coefficients 128 DESIGN PROCEDURES A Hardware Development Automation B Proximity Sensor Human Subject Human Face Microcontroller Image Acquisition Software Iris Qapture gt f web Camera Subject Human Eye Iris Image NIR LEDS Iris Recognitipn Algorithm Iris Segmentation Normalisation Template Encoding Template Matching Iris Template Database Enrollment Figure 3 1 Block Diagram The block diagram of the design is shown in figure 3 1 The automation part is composed of the proximity sensor the microcontroller and the image acquisition software This automation block as its name implies automates the capturing of the webcam through the use of the sensor that is connected to the microcontroller in which is handled by the image acquisition software The proximity sensor senses objects within 10cmrange from its transceiver The microcontroller used is the Gizduino microc
9. for i 2 19 a pinMode i output a digitalWrite i 0 a pinMode i input end catch ME disp but proceed anyway disp ME message disp Proceeding to deletion anyway end end fclose a aser end if it s an object delete it if isobject a aser delete a aser end end delete 61 disp displays the object function disp a display if isvalid a if isa a aser serial amp amp isvalid a aser disp a href matlab help arduino gt arduino lt a gt object connected to a aser port port if amots 1 disp Motor Shield Server running on the arduino board dent a servoStatus a motorSpeed a stepperSpeed den 7 disp Servo Methods a href matlab help servoStatus gt servoStatus lt a gt a href matlab help servoAttach gt servoAttach lt a gt lt a href matlab help servoDetach gt servoDetach lt a gt lt a href matlab help servoRead gt servoRead lt a gt lt a href matlab help servoWrite gt servoWrite lt a gt disp DC Motors and Stepper Methods a href matlab help motorSpeed gt motorSpeed lt a gt lt a href matlab help motorRun gt motorRun lt a gt lt a href matlab help stepperSpeed gt stepperSpeed lt a gt lt a href matlab help stepperStep gt stepperStep lt a gt else disp IO Server running on the arduino board dent a pinMode den disp Pin IO Methods a href matlab help pinMode gt pinMode lt a gt a href matlab help digit
10. fwrite a aser 57 57 uchar chk fscanf a aser d exit if there was no answer if isempty chk delete a error Connection unsuccessful please make sure that the Arduino is powered on running either adiosrv pde or mororsrv pde and that the board is connected to the indicated serial port You might also try to unplug and re plug the USB cable before attempting a reconnection end end check returned value if chk 1 disp Basic I O Script detected elseif chk 2 disp Motor Shield Script detected else delete a error Unknown Script Please make sure that either adiosrv pde or motorsrv pde are running on the Arduino end sets a mots flag a mots chk 1 set a aser tag a aser Tag ok initialize pin vector 1 is unassigned 0 is input 1 is output a pins 1 ones 1 19 initialize servo vector 1 is unknown 0 is detached 1 is attached 60 a srvs 0 ones 1 2 initialize motor vector 0 to 255 is the speed a mspd 0 ones 1 4 initialize stepper vector 0 to 255 is the speed a sspd 0 ones 1 2 notify successful installation disp Arduino successfully connected end arduino distructor deletes the object function delete a if it is a serial valid and open then close it if isa a aser serial amp amp isvalid a aser amp amp strcmpi get a aser Status open if isempty a aser Tag try trying to leave it in a known unharmful state
11. fy floor y cy ceil y tl inimage fy fx Value at top left integer pixel location tr inimage fy cx top right bl inimage cy fx bottom left br inimage cy cx bottom right upperavg tl hfrac or tr tl loweravg bl hfrac or br bl v2 upperavg vfrac or loweravg upperavg if inimage row col gt v2 This is a local maximum im row col inimage row col Record value in the output image end end end end 999999999999999999999999999999999999999999999999999999 99999 9 linecoords m linecoords returns the x y coordinates of positions along a line Usage x y linecoords lines imsize Arguments lines an array containing parameters of the line in form imsize size of the image needed so that x y coordinates are within the image boundary Output x X coordinates 89 corresponding coordinates function x y linecoords lines imsize xd 1 imsize 2 yd lines 3 lines 1 xd lines 2 coords find yd gt imsize 1 yd coords imsize 1 coords find yd lt 1 yd coords 1 int32 xd y int32 yd 999999999999999999999999999999999999999999999999999999999999 hysthresh m 9o HYSTHRESH Hysteresis thresholding Usage bw hysthresh im T1 T2 Arguments image to be thresholded assumed to be non negative T1 upper threshold value
12. governments military banks airports research laboratories and border control area This would allow and limit access to a particular information or area The government officials could also use this design for identifying and recording information of individuals and criminals Physical methods of identification which 42 includes anything requiring a password personal identification number or key for building access or the like are easily hacked or stolen but human iris cannot be stolen This technology addresses the problems of both password management and fraud 43 CHAPTER 5 CONCLUSION AND RECOMMENDATION CONCLUSION Based from the results obtained the design was proven sufficient for iris recognition The camera used is a manual focus CMOS camera In a Complementary Metal Oxide Semiconductor sensor each pixel has its own charge to voltage conversion and the sensor often includes amplifiers noise correction and digitalization circuits so that the chip outputs digital bits With these the design complexity increases and the area available for light capture decreases The correct positioning of the webcam NIR LEDs and sensor produced a clearer and brighter iris image which really improves the performance of the iris recognition system The NIR LEDs must be attached circular to the webcam so that noise that would be produced in the iris would be lessened The light of the NIR LEDs would be directed to the pupil Since
13. on iris recognition 11 Panganiban A 2009 CCD Camera with Near Infrared Illumination for Iris Recognition System 12 Panganiban A 2010 Implementation of Wavelet Algorithm for Iris Recognition System 134
14. 225 300 9oconvert to grayscale 8bit eyeimage rgb2gray eyeimage1 savefile eyeimage filename stat mess fileattrib savefile circleiris circlepupil imagewithnoise segmentiris eyeimage save savefile circleiris circlepupil imagewithnoise WRITE NOISE IMAGE imagewithnoise2 uint8 imagewithnoise imagewithcircles uint8 eyeimage get pixel coords for circle around iris x y circlecoords circleiris 2 circleiris 1 circleiris 3 size eyeimage ind2 sub2ind size eyeimage double y double x get pixel coords for circle around pupil xp yp circlecoords circlepupil 2 circlepupil 1 circlepupil 3 size eyeimage indi sub2ind size eyeimage double yp double xp 80 Write noise regions imagewithnoise2 ind2 255 imagewithnoise2 ind1 255 Write circles overlayed imagewithcircles ind2 255 imagewithcircles ind1 255 cd cd DIAGPATH imwrite imagewithcircles eyeimage_filename segmented jpg jpg cd w 9o perform normalisation polar array noise array normaliseiris imagewithnoise circleiris 2 circleiris 1 circleiris 3 circlepupil 2 circlepupil 1 circlepupil 3 eyeimage filename radial res angular res WRITE NORMALISED PATTERN AND NOISE PATTERN cd cd DIAGPATH imwrite polar_array eyeimage_filename polar jpg jpg cd w ENCODE THE TEMPLATE USING WAVELET output encode polar array noise arra
15. 50 8 and 204 C W MSOP junction to ambient Note 4 Supply current when output high typically 1 mA less at Voc 5V Note 5 Tested at Voc 5V and 15V Note 6 This will determine the maximum value of Ra Rg for 15V operation The maximum total RA Rg is 20 0 Note 7 No protection against excessive pin 7 current is necessary providing the package dissipation rating will not be exceeded Note 8 Refer to RETS555X drawing of military LM555H and LM555J versions for specifications www national com 4 112 February 2003 National Semiconductor LM567 LM567C Tone Decoder General Description High rejection of out of band signals and noise Immunity to false signals Highly stable center frequency Center frequency adjustable from 0 01 Hz to 500 kHz The LM567 and LM567C are general purpose tone decoders designed to provide a saturated transistor switch to ground when an input signal is present within the passband The circuit consists of an and Q detector driven by a voltage 8 controlled oscillator which determines the center frequency Applicatio ns of the decoder External components are used to indepen Touch tone decoding dently set center frequency bandwidth and output delay Precision oscillator Frequency monitoring and control Features Wide band FSK demodulation 20 to 1 frequency range with an external resistor Ultrasonic controls Logic compatible output with 100 mA current sinking Carrier current r
16. A blockade within 10cm range will have it output a low signal This sensor is used to send signal to the microcontroller for the program to allow the camera to take a picture whenever the sensor would detect that the person s iris to be captured is within the correct distance Furthermore the sensor is composed of capacitors resistors LM555 IC and LM567 IC 31 Figure 3 9 Gizduino Gizduino Microcontroller The Gizduino Microcontroller has 14 digital input output ports and 8 analog input output ports The output port of the proximity sensor is connected to one of its digital input output ports It also has 3 ground pins 5 V pin and 3 3 V pin Figure 3 10 Webcam Webcam The camera used is the a4tech PK 710mj live messenger 5M Webcam It is connected to the USB port of the computer A manual focused camera was used so that the correct distance of the person s iris to the lens of the camera may be set specifically in a way the eye of the person would only be captured by the 32 camera the focus range is set about 4cm In this case the image being captured by the camera is stable in terms of how far the eye is from the camera to distinguish accurately the iris to be segmented and recognized Camera Specification Image Sensor 4 CMOS 640x480pixels e Frame Rate 15fps 640x480 600x800 30fps 320x240 160x120 e Lens F 2 2 f 4 6mm e View Angle 65 degree e Focus Range Manual Focus 2cm to infinity e Exposure C
17. Gizmo The image acquisition software is developed using MATLAB R2009a The next part is the Iris Capture block It consists of the webcam and the NIR LEDs The webcam is connected to the computer through its USB cord The NIR LEDs are the one responsible for the visibility of the iris to the webcam If the image acquisition software tells the webcam to capture the webcam will do so and an iris image will be produced The final part is the iris recognition algorithm The iris recognition algorithm starts with the iris segmentation process It is based on the circular Hough transform which is similar to the equation of a circle X c Y c r Since the iris of the eye is ideally shaped like a circle the Hough transform is used to determine the properties of geometric objects found in an image like circles and lines Canny edge detection is used to detect edges of shapes It is developed by John F Canny in 1986 Horizontal lines are drawn on the top and bottom eyelid to separate the iris and two circles are drawn one for the pupil and the other one for the iris The value of the iris radius to be used ranges from 75 to 85 pixels and for the pupil radius ranges from 20 to 60 pixels After the iris is segmented it is normalized In normalization the segmented iris is converted to a rectangular shaped strip with fixed dimensions This process uses Daugman s rubber sheet model The image will then be analyzed using 2D wavelets at maximum level o
18. No light 8 No light 9 No light 10 No light As seen in Table 4 2 the correctness of the distance and position was seen on the red LED s intensity with respect to the settings indicated in table 4 1 A solid red light was seen when an object is to 4m away from the IrDA But a flickering red light was seen when the range is within the range of 4cm to 5cm The LED does not produce light when the object is greater than 5cm Also these findings were relevant to the behaviour of the camera When the red LED has a solid light the camera captures every time an object is sensed 35 IMAGE QUALITY TEST The performance of the iris recognition system particularly recognition and segmentation and the interoperability are highly dependent in the quality of the iris image Table 4 3 Camera Specifications A4tech PK 710 live Specifications CCD Camera messenger 5M Webcam CCD image sensor with Image Sensor validity pixel of PAL 512x528 512x492 CMOS image sensor 640x480pixels Manual Focus 2cm to infinity according to user requirement Manual focus according Focus Range to user requirement Our group replaced Eng r Panganiban s CCD Camera with a CMOS Camera The camera must possess excellent imaging performance in order to produce accurate results In a CCD Charge Couple Device sensor every pixel s charge is transferred through a very limited number of output nodes to be
19. a analogWrite 11 90 sets pin 11 to 90 255 a analogWrite 3 10 sets pin 3 to 10 255 9 59 59 59 69 59 69 59 09 69 69 o9 09 o9 09 09 09 o9 09 o9 09 o9 69 o9 569 9 ARGUMENT CHECKING o check nargin if narginv 3 70 error Function must have the pin and val arguments end first argument must be the arduino variable if isa a arduino error The first argument must be an arduino variable end check pin errstr arduino checknum pin pwm pin number 3 5 6 9 10 11 if isempty errstr error errstr end check val errstrzarduino checknum val analog output level 0 255 if isempty errstr error errstr end pin should be configured as output if a pins pin 1 warning MATLAB Arduino analogWrite TTT digital pin num2str pin is set as input pwm output takes place only after using a pinMode num2str pin output 1 end 9o check a aser for validity errstrzarduino checkser a aser valid if isempty errstr error errstr end 9 59 59 59 69 59 69 69 09 69 69 09 09 9 09 69 09 o9 09 69 69 o9 09 09 099 PERFORM ANALOG OUTPUT 00000000 0 0 00 00 00 00 00 0 0 00 0 0 00 07 7 00 0 0 0 07 00 0 0 000 0 if strcempi get a aser handle demo mode average analog output delay pause 0 0088 else check a aser for openness errstr arduino checkser a aser open if isempty errstr error errstr end 9o
20. accuracy of the iris templates in our design the Degrees of Freedom DoF was computed The computed DoF of our design is 80 which is higher than that of Engr Panganiban s work Keywords biometrics iris recognition hamming distance wavelet real time image processing I DESIGN BACKGROUND AND INTRODUCTION Biometrics is becoming popular nowadays due to its very useful security applications The technology uses the unique characteristics of an individual in an electronic system for authentication Biometric technologies used as a form of identity access management and access control are becoming the foundation of an extensive array of highly secure identification and personal verification solutions There are several of applications for biometrics which include civil identity infrastructure protection government public safety and the like As for the main intention of this design is to implement it for security function since it is very useful to this field having a fact that an iris of a human is the most unique even for a person the left iris has different pattern of wavelets compared to that of the right iris of the same person This design includes an automated CMOS camera and proximity sensor for iris recognition system A CMOS camera or complementary metal oxide semiconductor camera has a CMOS image sensor in which has an ability to integrate a number of processing and control functions These features include timing logi
21. are provided together with reliable measurements or data that will support the researcher s remarks SENSOR OUTPUT TEST The proximity sensor automates the system by detecting whether the person is at the correct distance and position before capturing the subject s iris Further testing on the proximity sensor was done because there has been a suspected glitch found on the proximity sensor Table 4 1 Proximity Sensor Settings Red LED Status Output Solid Red Light Solid Red Light Solid Red Light Solid Red Light Flickering Red Light No light No light No light Table 4 2 Sensor Output Testing As seen in Table 4 2 the correctness of the distance and position was seen on the red LED s intensity with respect to the settings indicated in table 4 1 A solid red light was seen when an object is to 4m away from the IrDA But a flickering red light was seen when the range is within the range of 4cm to 5 The LED does not produce light when the object is greater than 5cm Also these findings were relevant to the behaviour of the camera When the red LED has a solid light the camera captures every time an object is sensed IMAGE QUALITY TEST The performance of the iris recognition system particularly recognition and segmentation the interoperability are highly dependent in the quality of the iris image A4tech PK 710mj live CCD image sensor with CMOS sensor validity pixel o
22. converted to voltage buffered and sent off chip as an analog signal All of the pixel can be devoted to light capture and the uniformity of the output is high In a CMOS Complementary Metal Oxide Semiconductor sensor each pixel has its own charge to voltage conversion and the sensor often includes amplifiers noise correction and digitalization circuits so that the chip outputs digital bits With these the design complexity increases and the area available for light capture decreases The uniformity is lower because each pixel is doing its own 36 conversion Also both cameras that were used were manual focus for the user to adjust it to their system s requirements Figure 4 1 Selected iris images from Engr Panganiban s system 37 Figure 4 2 Selected iris images from the current system Table 4 4 Iris Image Quality Assessment Common Quality Metrics Figure 4 1 Figure 4 2 Blur Motion Blurred Image Clear Image Noise in the Iris Image With Noise Without Noise Brightness Dark Bright Magnification Blurred Image Clear Image In Table 4 4 it can be observed that the improved design really showed promising results The design produced a clear and bright image even though the image was magnified in the test The magnification testing was made by zooming in the images Also there was no noise in the iris image 38 Table 4 5 Enrolled Captured Iris Images ID Number Ir
23. dissipation Warmewiderstand freie Beinchenlange Rinsa 375 K W max 10 mm Thermal resistance lead length between package bottom and PC board max 10 mm 2000 01 01 2 OPTO SEMICONDUCTORS Infineon technologies OSRAM 115 SFH 484 SFH 485 Kennwerte 7 25 C Characteristics Bezeichnung Symbol Wert Einheit Parameter Symbol Value Unit Wellenlange der Strahlung peak 880 nm Wavelength at peak emission I 100 mA Spektrale Bandbreite bei 50 von Le AX 80 nm Spectral bandwidth at 50 of Le I 100 Abstrahlwinkel Half angle SFH 484 8 Grad SFH 485 20 deg Aktive Chipflache A 0 09 mm Active chip area Abmessungen der aktiven Chipflache LxB 0 3 x 0 3 mm Dimension of the active chip area LxW Abstand Chipoberflache bis Linsenscheitel Distance chip front to lens top SFH 484 H 5 31 5 4 mm SFH 485 H 4 2 4 8 mm Schaltzeiten I von 10 auf 90 und von 90 f f 0 6 0 5 us auf 10 bei 100 mA 50 Q Switching times I from 10 to 90 and from 90 to 10 J 100 mA R 500 Kapazitat Ca 15 pF Capacitance Vk 0 f 1 MHz Durchla amp spannung Forward voltage I 100 mA t 20 ms Ve 1 50 x 1 8 V Ip 1 t 100 ps Ve 3 00 lt 3 8 V Sperrstrom In 0 01 x 1 Reverse current He zz DV GesamtstrahlungsfluB 25 mW Total radiant flux Ig 100 i 20 ms 2000 01 01 3 OPTO SEMICONDUCTORS
24. distance values as binomial distribution FAR False Accept Rate is the probability that the system incorrectly matches the input pattern to the non matching template in the database The FRR False Reject Rate is the probability that the system fails to detect a match between the input pattern and a matching template in the database The ROC Relative Operating Characteristic plot is the visual characterization of the trade off between the FAR and FRR The EER Equal Error Rate is the rate at which both accept and reject errors are equal Panganiban 2010 determined the performance of each feature of the vector in terms of the accuracy over vector length The threshold values were identified through the range of the Hamming distance Poor Quality means that the Hamming distance value is 10 lower than the threshold value Moderate Quality means that the user has to decide whether the Hamming distance value agrees with the desired result This occurs when the value is 10 of the threshold values Good Quality means that the Hamming 40 distance value is 10 higher than the threshold value False Accept Rate FAR is the probability that the system accepts an unauthorized user or a false template which is computed using the formula FAR Gest where Pinter is the number of HD 17 values that fall under Poor Quality of the inter class distribution and n is the total number of samples False Reject Rate FRR is the probability that the system
25. frame F tempimage bmp 9osave set handles statusLbl String Saving imwrite frame F Pictures tempimage bmp imwrite frame F Pictures tempimagel1 bmp match set handles statusLbl String Searching for matches output irisrecognitionprocess F tempimage bmp set handles statusLbl String Searching Completed frmAddName conn database thesis sa mssql cursor exec conn select IrisId IrisTemplate from IrisDataBankDesign cursor fetch cursor intmax size cursor data 1 mati output output mat2str mat1 mati str2mat output irisfound 0 threshold 0 1000 int 0 for int 1 intmax mat2 str2mat cursor data int 2 HD gethammingdistance mat1 mat2 HD_values int HD statusIBI HD if HD gt 0 amp HD lt threshold irisfound 1 end end set handles HdListbox String HD values close cursor close conn if irisfound msgbox Authenticated IRIS RECOGNITION else msgbox Iris Not Authenticated IRIS RECOGNITION myWait 2 set handles EnrollBtn Enable on end end match else set handles statusLbl String Idle end 78 end Choose default command line output for untitled handles output hObject Update handles structure guidata hObject handles UIWAIT makes untitled wait for user response see UIRESUME uiwait handles figure1 Outputs from this function are returned to the co
26. max layer if maxlayer gt maxtotal maxtotal maxlayer r int32 lradsc i scaling row col find layer maxlayer 95 row int32 row 1 scaling returns only first max value col int32 col 1 scaling end end 9 999999999999999999999999999999999999999999999999999999999 9 9 99 circlecoords m findcircle returns the coordinates of a circle in an image using the Hough transform and Canny edge detection to create the edge map Usage row col r findcircle image lradius uradius scaling sigma hithres lowthres vert horz Arguments image the image in which to find circles radius lower radius to search for 9o uradius upper radius to search for 9o scaling scaling factor for speeding up the Hough transform sigma amount of Gaussian smoothing to apply for creating edge map 9o hithres threshold for creating edge map 9o lowthres threshold for connected edges vert vertical edge contribution 0 1 9o horz horizontal edge contribution 0 1 Output 9o circleiris centre coordinates and radius of the detected iris boundary circlepupil centre coordinates and radius of the detected pupil boundary imagewithnoise original eye image but with location of noise marked with NaN values function row col findcircle image lradius uradius scaling sigma hithres lowthres vert horz 96 Iradsc
27. meshgrid 1 size image 2 1 size image 1 polar array interp2 x y image xo yo create noise array with location of NaNs in polar array polar noise zeros size polar array coords find isnan polar array polar noise coords 1 103 polar_array double polar_array 255 start diagnostics writing out eye image with rings overlayed get rid of outling points in order to write out the circular pattern coords find xo gt size image 2 xo coords size image 2 coords find xo lt 1 xo coords 1 coords find yo gt size image 1 yo coords size image 1 coords find yo lt 1 yo coords 1 round xo yo round yo xo int32 xo yo int32 yo indi sub2ind size image double yo double xo image uint8 image image ind1 255 get pixel coords for circle around iris x y circlecoords x_iris y_iris r_iris size image ind2 sub2ind size image double y double x get pixel coords for circle around pupil xp yp circlecoords x pupil y pupil r pupil size image indi sub2ind size image double yp double xp image ind2 255 image ind1 255 write out rings overlaying original iris image cd cd DIAGPATH imwrite image eyeimage_filename normal jpg jpg 104 cd w end diagnostics replace NaNs before performing feature encoding coords find isnan polar_array polar_array2 polar_array
28. on computer a systematically arranged collection of computer data structured so that it can be automatically retrieved or manipulated De noising the extraction of a signal from a mixture of signal and noise Enrolment the process of putting something on a database for the first time Focus the point where rays of light heat etc or waves of sound come together or from which they spread or seem to spread specifically the point where rays of light reflected by a mirror refracted by a lens meet or the point where they would meet if prolonged backward through the lens or mirror Hamming distance the difference between letter or number sequences a measure of the difference between two words or messages expressed by the number of characters needing to be changed in one message to obtain the other Hardware physical components of a computer system Illumination an act of illuminating the provision of light to make something visible or bright or the fact of being lit up Image a picture idea or impression of a person thing or idea or a mental picture of a person thing or idea Image acquisition image processing the alteration or manipulation of images that have been scanned or captured by a digital recording device Image capture employing a device such as a scanner to create a digital representation of an image Image quality used to refer to the degree of visibility
29. position his or her eye properly to the device Also the results showed that when the Hamming distance value is greater than or equal to 0 1060 the iris templates do not match The Intra class comparison of Haar Wavelet at level 4 vertical coefficient shows that when the HD value is less than 0 1060 the iris templates are from the same individual From the results of the Hamming Distance in inter class comparison the Degrees of Freedom DoF computed is 80 133 which is higher than of Engr Panganiban s work which is equal to 50 This shows that the comparison of iris templates in our design is more accurate B Recommendation Although the obtained results proved that the design is sufficient for iris recognition the following are still recommended for the improvement of the system s performance 1 The proximity sensor may be replaced by an algorithm such as pattern recognition that will allow the software to capture the iris image once a circular shape is near the camera 2 The digital camera can be converted to an Infrared Camera which would replace the webcam and NIR LEDs 3 Artificial Intelligence such as Fuzzy Logic can be applied to the system to improve the performance of the Iris recognition system 4 Embedding the Iris recognition system its hardware and software into one device can be done to have the speed of the system independent on the speed of the computer used and could also be portable REFEREN
30. program and choose Run File to run this program 52 How to setup the Iris Recognition Design Note The Iris Recognition software must be properly referenced on MATLAB and the arduino code provided must be uploaded on the arduino microcontroller 1 Plug in the source to 220 V supply and the USB cable to the Computer or Laptop Be sure that the computer being used complies with the design s system requirements 2 Make sure that the arduino input output server code is uploaded to the microcontroller and the Iris Recognition Software is on the current directory on MATLAB 3 Open MATLAB R2009a highlight all folders under Iris Recognition System folder Software Design then right click Choose add to path gt all folders and sub folders Then run the Matlab program 4 Run the MATLAB software irisrecognition m provided 5 Adjust the position of the Camera and IR LEDs to where the subject is comfortable with just be sure that it would capture the subject s iris image accurately Then compile and run the MATLAB program of iris recognition system 6 The User must move his her head close to the camera within the proximity range 4 to 5 cm away From here the design must perform its auto capture and real time process of data 53 7 If the iris image captured isn t within the authenticated list on the database the user will be asked to whether or not enrol the iris image Otherwise the program will
31. simply display unauthenticated iris image pattern 8 After the authentication the program will go back to its status of auto capturing an iris image 9 To terminate simply exit the MATLAB program IV Troubleshooting Guides and Procedures 1 If there is a problem on the Arduino Connection on MATLAB a Upload the adiosrv pde on the Gizduino b Check if the COM PORT where the Gizduino is connected is the same on the SerialPort definition on MATLAB 2 If the image is blurred check and adjust the focus of the camera Twist its lens to have the desired focus 3 Uploading Errors on Gizduino a Check the syntax for errors b Consult the website www arduino cc for more information 4 Unknown MATLAB function a Check if the program files are located at the current directory window of MATLAB 54 b If the files are already the current directory of MATLAB select all files and right click then add to path all the folders and subfolders 5 If there are many cameras connected and installed on the laptop check the image acquisition toolbox of MATLAB and select the adaptor name and device ID of the desired camera to be used 6 There is no light emitted by the LEDs a Make sure that the polarity on the source to LED connection is correct b Check the proper connection of the LEDs in series and parallel c Plug the power supply V Error Definitions MATLAB 1 Error in using videoinput in MATLAB The camera device is
32. specified in Chapterl This chapter also tackles the important results of the test performed in Chapter 4 including the limitations of the design The recommendation part of this chapter suggests what should be done to improve the design A Conclusion Based from the results obtained the design was proven sufficient for iris recognition The camera used is a manual focus CMOS camera In a Complementary Metal Oxide Semiconductor sensor each pixel has its own charge to voltage conversion and the sensor often includes amplifiers noise correction and digitalization circuits so that the chip outputs digital bits With these the design complexity increases and the area available for light capture decreases The correct positioning of the webcam NIR LEDs and sensor produced a clearer and brighter iris image which really improves the performance of the iris recognition system The NIR LEDs must be attached circular to the webcam so that noise that would be produced in the iris would be lessened The light of the NIR LEDs would be directed to the pupil Since the light reflection will be located in the pupil it would not affect the iris segmentation and that the iris template The case of the camera also lessens the noise since it blocks other factors that might affect the iris image and results The proximity sensor has a delay of 5 seconds before it sends signal for the webcam to capture the iris image There is a delay so that the user can
33. the display position get handles frmAddName Position position 1 screenSize 3 position 3 2 82 position 2 screenSize 4 position 4 2 center the window set handles frmAddName Position position Outputs from this function are returned to the command line function varargout frmAddName OutputFcn hObject eventdata handles Get default command line output from handles structure varargout 1 handles output function txtName_Callback hObject eventdata handles Executes during object creation after setting all properties function txtName_CreateFcn hObject eventdata handles if ispc set hObject BackgroundColor white else set hObject BackgroundColor get 0 defaultUicontrolBackgroundColor end Executes on button press in btnOK function btnOK_Callback hObject eventdata handles frame imread F Pictures tempimage bmp HH findobj gcf Tag txtName ID get HH String IDcat strcat F Pictures ID filename strcat IDcat jpg if exist filename file errordlg Name already exist Information return else imwrite frame filename JPG output irisrecognitionprocess filename conn database thesis sa mssql colnames IrisPath IrisTemplate output mat2str output exdata filename output 83 insert conn iris dbo IrisDataBankDesign colnames exdata end close conn cl
34. the isolation of the eyelashes and reflections The segmented iris region was normalised by implementing Daugman s rubber sheet model The iris is modelled as a flexible rubber sheet which was unwrapped into a rectangular block with constant polar dimensions to eliminate dimensional inconsistencies between iris regions Then the features of the iris were encoded by convolving the normalised iris region with 1D Log Gabor filters and phase quantising the output in order to produce a bit wise biometric template The Hamming distance was chosen as a matching metric This gave a measure on the number of bits that disagreed between two templates A failure of statistical independence between two templates would result in a match This means that the two templates were considered to have been generated from the same iris if the Hamming distance produced was lower than a set Hamming distance In the proposed algorithm of Panganiban 2010 the feature vector was encoded using Haar and Biorthogonal wavelet families at various levels of decomposition Vertical coefficients were used for implementation because of the dominant features of the normalized images that were oriented vertically 15 Hamming distance was used to define the inter class and intra class relationships of the templates The computed number of degrees of freedom which was based on the mean and the standard deviation of the binomial distribution demonstrated the separation of iris classe
35. 2 error checknum third argument must be a cell with at least 2 entries end initialize error string errstr check string for type if ischar str errstr The description argument must be a string return end check string for size if numel str lt 1 errstr The description argument cannot be empty return end check str against allowed values if any strcmpi str allowed make sure this is a hozizontal vector allowed allowed add a comma at the end of each value 74 for i 1 length allowed 1 allowed i allowed i end form error string errstr Unallowed value for description the value must be either allowed 1 end 1 allowed end return end end checkstr function errstr checkser ser chk errstr arduino checkser ser chk Checks serial connection argument This function checks the first argument ser to make sure that either 1 it is a valid serial connection if the second argument is valid 3 it is open if the second argument is open If the check is successful then the returned argument is empty otherwise it is a string specifying the type of error preliminary check nargin if narginv 2 error checkser needs two arguments please read the help end initialize error string errstr check serial connection switch lower chk case valid make sure is a serial port if isa ser serial
36. 215 C 220 C See AN 450 Surface Mounting Methods and Their Effect on Product Reliability for other methods of soldering surface mount devices ojo www national com 111 SSSIN1 LM555 Electrical Characteristics Notes 1 2 Continued 25 C Voc 5V to 15V unless othewise specified Parameter Conditions Output Voltage Drop Low Voc 15V Lou 10 Lou 50mA Isink 100 Lou 200mA Voc DN Lane 8mA Lane SMA Output Voltage Drop High lsource 200mA Voc 15V Isounce 100mA Voc 15V Voc 5V Rise Time of Output Fall Time of Output Note 1 All voltages are measured with respect to the ground pin unless otherwise specified Note 2 Absolute Maximum Ratings indicate limits beyond which damage to the device may occur Operating Ratings indicate conditions for which the device is functional but do not guarantee specific performance limits Electrical Characteristics state DC and AC electrical specifications under particular test conditions which guarantee specific performance limits This assumes that the device is within the Operating Ratings Specifications are not guaranteed for parameters where no limit is given however the typical value is a good indication of device performance Note 3 For operating at elevated temperatures the device must be derated above 25 C based on a 150 C maximum junction temperature and a thermal resistance of 106 C W 170 C W
37. 268 0 1227 0 1227 0 1268 0 1206 0 1538 0 1289 0 0000 0 1227 0 1102 0 1185 0 1331 0 1372 0 1081 0 1143 0 1435 0 1393 0 1227 0 0000 0 1123 0 1206 0 1081 0 1372 0 1247 0 1227 0 1351 0 0977 0 1102 0 1123 0 0000 0 1206 EK 0 0 1206 0 1414 0 1372 0 1060 0 1310 0 1268 0 1185 0 1206 0 1206 0 0000 It is observable that when the Hamming distance value is greater than or equal to 0 1060 the iris templates do not match In table 4 6 the Intra class comparisons of Haar Wavelet at level 4 vertical coefficient shows that when the HD value is less than 0 1060 the iris template are from the same individual Using the formula for the degrees of freedom 1 p pom E Cr Where p is the mean which is equal to 0 1261 and the o is the standard deviation which is equal to 0 03954 the number of degrees of freedom is 80 According to statistics this is the number of degrees of freedom that the values in this case the HD values are free to vary 41 Table 4 7 Intra class comparisons of Haar wavelet at Level 4 vertical coefficient Iris 1 2 3 4 5 6 7 8 9 10 Id m 0 0811 0 1351 0 1310 0 1060 0 1123 0 1247 0 1227 0 1289 0 1185 0 1227 0 1310 0 0603 0 1019 0 1185 0 1331 0 1123 0 1268 0 1289 0 1435 0 1227 0 1310 0 1310 0 0686 0 1351 0 1372 0 12
38. 47 0 1476 0 1081 0 1227 0 1019 0 1164 0 1331 0 1497 0 0956 0 1268 0 1393 0 1247 0 1310 0 1123 0 104 0 1247 0 1206 0 1455 0 1247 0 0852 0 1060 0 1372 0 1351 0 1206 0 1518 0 1372 0 1206 0 1081 0 1289 0 1185 0 0520 0 1372 0 1227 0 0915 0 1372 0 1164 0 1164 0 1164 0 1080 0 1310 0 1393 0 0873 0 1185 0 1164 0 1206 0 1310 0 1518 0 1268 0 1310 0 1580 0 1060 0 1227 0 0748 0 1227 0 1227 0 1102 0 1435 0 1185 0 1019 0 1289 0 1123 0 1435 0 1164 0 0561 0 1143 0 0 0 1019 0 1227 0 1476 0 1143 0 1455 0 1247 0 0977 0 1247 0 1143 0 0977 IMPACT ANALYSIS The iris recognition system of Engr Panganiban was taken to the next level by adding real time image processing features to it This would be easier to use for the user would just look into the camera and wait for just a short period of time for the system to capture and process his or her iris After the image was processed it would immediately display if the person is authenticated or not The designed iris recognition showed an increasing promise on the security system for it analyses the unchanging measurable biological characteristics that are unique to each individual The design can be used as a prototype which can be implemented by in places demanding high security such as companies
39. AUTOMATED IRIS RECOGNITION SYSTEM USING CMOS CAMERA WITH PROXIMITY SENSOR by Paulo R Flores Hazel Ann T Poligratis Angelo S Victa A Design Report Submitted to the School of Electrical Engineering Electronics Engineering and Computer Engineering in Partial Fulfilment of the Requirements for the Degree Bachelor of Science in Computer Engineering Mapua Institute of Technology September 2011 Approval Sheet Mapua Institute of Technology School of EECE This is to certify that we have supervised the preparation of and read the design report prepared by Paulo R Flores Hazel Ann T Poligratis and Angelo S Victa entitled Automated Iris Recognition System Using CMOS Camera with Proximity Sensor and that the said report has been submitted for final examination by the Oral Examination Committee al G ee S Design Adviser As members of the Oral Examination Committee we certify that we have examined this design report presented before the committee on September 10 2011 and hereby recommended that it be accepted in fulfilment of the design requirements for the degree in Bachelor of Science in Computer Engineering Engr Dionis A Padilla Engr Joshua B Cuesta Panel Member Panel Member This design report is hereby approved and accepted by the School of Electrical Engineering Electronics Engineering and Computer Engineering in partial fulfilment of the requirements for the degree in Bachelor of Science in Com
40. CES 1 Addison P 2002 The Illustrated Wavelet Transform Handbook Institute of Physics 2 Bradley J Brislawn C and Hopper T 1993 The FBI Wavelet Scalar Quantization Standard for Gray scale Fingerprint Image Compression Tech Report LA UR 93 1659 Los Alamos Nat l Lab Los Alamos N M 3 Boles W W and Boashash B A 1998 A human identification technique using images of the iris and wavelet transform IEEE trans on signal processing vol 46 issue 4 4 Canny J 1986 A Computational Approach To Edge Detection IEEE Trans Pattern Analysis and Machine Intelligence 8 679 714 5 Cohn J 2006 Keeping an Eye on School Security The Iris Recognition Project in New Jersey Schools NIJ Journal no 254 6 Huifang and Guangshu 2005 Iris recognition based on adjustable scale wavelet transform Proceedings of the 2005 IEEE 7 Kong W and Zhang D 2001 Accurate iris segmentation based on novel reflection and eyelash detection model Proceedings of 2001 International Symposium on Intelligent Multimedia Video and Speech Processing Hong Kong 8 Makram Nabti and Bouridane 2007 An effective iris recognition system based on wavelet maxima and Gabor filter bank IEEE trans on iris recognition 9 Masek L 2003 Recognition of Human Iris Patterns for Biometric Identification 10 et al 2007 iris recognition based on dual tree complex wavelet transform IEEE trans
41. EN 01081 0437 0 1247 0 1227 0458 0497 01102 01722 0999 0 120 10 0 1206 0 1414 0 1372 0 1060 0 1310 0 1268 0 1185 0 1206 0 1206 0 0000 Table 4 6 Inter class Comparisons of Haar Wavelet at Level 4 Vertical Coefficient It is observable that when the Hamming distance value is greater than or equal to 0 1060 the iris templates do not match In table 4 6 the Intra class comparisons of Haar Wavelet at level 4 vertical coefficient shows that when the HD value is less than 0 1060 the iris template are from the same individual Using the formula for the degrees of freedom por 24 D Where p is the mean which is equal to 0 1261 and the o is the standard deviation which is equal to 0 03954 the number of degrees of freedom is 80 According to statistics this is the number of degrees of freedom that the values in this case the HD values are free to vary ef fF pr p ee P EPE ld 0 1351 01310 0 1247 01227 0 1285 0 1185 0 1435 3 04312 0 1247 4 0 1164 0 1331 0 1497 0 1268 0 1393 0 1247 0 1310 5 0 1247 0 1206 0 1455 0 1247 0 0852 0 1060 0 1372 0 1351 0 1206 0 1518 6 0 1372 0 1206 0 1081 0 1289 0 1185 0 0520 0 1372 0 1227 0 0915 0 1372 8 0 31 24518 01268 0 1310 0 1580 0 1060 0 7227 0 0788 0 1227 01227 3 0 1102 0 1435 0 1185 0121 0 1289 0 1123 0 1435 0 1164 0 0561 0 1143 Table 4 7 Intra class Comparisons of H
42. OLOGY IMAGE QUALITY IMAGE QUALITY METRICS PROXIMITY SENSOR IRIS IMAGE ACQUISITION vi vii viii 10 10 11 11 14 14 IRIS RECOGNITION SYSTEM AND PRINCIPLES 15 BIOMETRIC TEST METRICS 16 Chapter 3 DESIGN PROCEDURES 19 HARDWARE DEVELOPMENT 20 SOFTWARE DEVELOPMENT 26 PROTOTYPE DEVELOPMENT 28 Chapter 4 TESTING PRESENTATION AND INTERPRETATION OF DATA 34 SENSOR OUTPUT TEST 34 IMAGE QUALITY TEST 36 DATASETS 40 IMPACT ANALYSIS 42 Chapter 5 CONCLUSION AND RECOMMENDATION 44 BIBLIOGRAPHY 47 APPENDIX 49 APPENDIX A Operation s Manual 49 APPENDIX B Pictures of Prototype 57 APPENDIX C Program Listing 58 APPENDIX D Data Sheets 108 APPENDIX E IEEE Article Format 124 LIST OF TABLES Table 4 1 Proximity Sensor Settings Table 4 2 Sensor Output Testing Table 4 3 Camera Specifications Table 4 4 Iris Image Quality Assessment Table 4 5 Enrolled Captured Iris Images Table 4 6 Inter class comparisons of Haar wavelet at Level 4 vertical coefficient Table 4 7 Intra class comparisons of Haar wavelet at Level 4 vertical coefficient 34 35 36 38 40 41 42 vi LIST OF FIGURES Figure 2 1 Iris Diagram Figure 3 1 Conceptual Framework Figure 3 2 Block Diagram Figure 3 3 Schematic Diagram Figure 3 4 System Flowchart Figure 3 5 Relational Model Figure 3 6 5 V Power Supply Figure 3 7 NIR LED Figure 3 8 Proximity Sensor Figure 3 9 Gizduino Figure 3 10 Webca
43. The FRR False Reject Rate is the probability that the system fails to detect a match between the input pattern and a matching template in the database The ROC Relative Operating Characteristic plot is the visual characterization of the trade off between the FAR and FRR The EER Equal Error Rate is the rate at which both accept and reject errors are equal Panganiban 2010 determined the performance of each feature of the vector in terms of the accuracy over vector length The threshold values were identified through the range of the Hamming distance Poor Quality means that the Hamming distance value is 10 lower than the threshold value Moderate Quality means that the user has to decide whether the Hamming distance value agrees with the desired result This occurs when the value is 10 of the threshold values Good Quality means that the Hamming 40 distance value is 10 higher than the threshold value False Accept Rate FAR is the probability that the system accepts an unauthorized user or a false template which is computed using the formula FAR P 4 n where Pinter is the number of HD values that fall under Poor Quality of the inter class distribution and n is the total number of samples False Reject Rate FRR is the probability that the system rejects an authorized user or a correct template which is computed using the formula FRR Pintra n where Pinta is the number of HD values that fall under Poor Quality of the intra class
44. aar Wavelet at Level 4 Vertical Coefficient A Impact Analysis The iris recognition system of Engr Panganiban was taken to the next level by adding real time image processing features to it This would be easier to use for the user would just look into the camera and wait for just a short period of time for the system to capture and process his or her iris After the image was processed it would immediately display if the person is authenticated or not The designed iris recognition showed increasing promise on the security system for it analyses the unchanging measurable biological characteristics that are unique to each individual The design can be used as a prototype which can be implemented by in places demanding high security such as companies governments military banks airports research laboratories and border control area This would allow and limit access to a particular information or area The government officials could also use this design for identifying and recording information of individuals and criminals Physical methods of identification which includes anything requiring a password personal identification number or key for building access or the like are easily hacked or stolen but human iris cannot be stolen This technology addresses the problems of both password management and fraud V CONCLUSIONS AND RECOMMENDATION This chapter gives the overall conclusion of the design covering up all the objectives
45. al pins from 0 to 13 are located on the upper right of the board while the digital pins from 14 to 19 are better known as analog input pins and are located in the lower right corner of the Examples a digitalWrite 13 1 sets pin 13 high a digitalWrite 13 0 sets pin 13 low 00 000 Y 00 00 0 0 00 0 00 00 0000000000 00 00000000 00000000 ARGUMENT CHECKING check nargin if narginv 3 error Function must have the and val arguments end first argument must be the arduino variable if isa a arduino error The first argument must be an arduino variable end check pin errstrzarduino checknum pin pin number 2 19 if isempty errstr error errstr end check val errstrzarduino checknum val value 0 1 if isempty errstr error errstr end 9o pin should be configured as output if a pins pin 1 67 warning MATLAB Arduino digitalWrite If digital pin num2str pin is set as input digital output takes place only after using a pinMode num2str pin output 1 end 9o check a aser for validity errstr arduino checkser a aser valid if isempty errstr error errstr end 9 00 00 9009 009009 909 00 00 Din D n Din Die O Dn Din O PERFORM DIGITAL OUTPUT M M M if strempi get a aser Port 9o handle demo mode average digital output delay pause 0 0087 else chec
46. alRead digitalRead a a href matlab help digitalWrite gt digitalWrite lt a gt a href matlab help analogRead gt analogRead lt a gt lt a href matlab help analogWrite gt analogWrite lt a gt end disp else disp lt a href matlab help arduino gt arduino lt a gt object connected to an invalid serial port disp Please delete the arduino object disp end else 62 disp Invalid a href matlab help arduino gt arduino lt a gt object disp Please clear the object and instantiate another one disp end end pin mode changes pin mode function pinMode a pin str a pinMode pin str specifies the pin mode of a digital pins The first argument before the function name a is the arduino object The first argument pin is the number of the digital pin 2 to 19 9o The second argument str is a string that can be input or output Called with one argument as a pin pin it returns the mode of the digital pin called without arguments prints the mode of all the digital pins Note that the digital pins from 0 to 13 are located on the upper right part of the board while the digital pins from 14 to 19 are better known as analog input pins and are located in the lower right corner of the board Examples a pinMode 11 output sets digital pin 11 as output 9o a pinMode 10 input sets digital pin 10 as input 9o valza pinMode 10 return
47. argin if narginv 2 error Function must have the pin argument end first argument must be the arduino variable if isa a arduino error The first argument must be an arduino variable end check pin errstrzarduino checknum pin pin number 2 19 if isempty errstr error errstr end check a aser for validity errstr arduino checkser a aser valid if isempty errstr error errstr end 00 00 00 0 0 0 o 0 0 0000 00 Din D n Din Die Din Dn Din O PERFORM DIGITAL INPUT 00000060000 00 0 0 00 0 0 D n Din D n Din 00 00 D n D n Din 0000 00 00 00 Din D n Din if strempi get a aser Port DEMO 9o handle demo mode 9o average digital input delay pause 0 0247 output 0 or 1 randomly val round rand else check a aser for openness errstr arduino checkser a aser open if isempty errstr error errstr end send mode and pin fwrite a aser 49 97 pin uchar get value val fscanf a aser Yod end 66 end digitalread digital write function digitalWrite a pin val part board a digitalWrite pin val performs digital output on a given pin The first argument before the function name a is the arduino object 9o The second argument pin is the number of the digital pin 2 to 19 9o where the digital output needs to be performed 9o The third argument val is the value either 0 or 1 for the output Note that the digit
48. aw circles of different radii for index 1 size y x index 92 cy y index for 1 h n addcircle h n cx cy n rmin end end 9 9999999999999999999999999999999999999999999999999999999 999 9 99 findline m findline returns the coordinates of a line in an image using the linear Hough transform and Canny edge detection to create the edge map Usage lines findline image Arguments image the input image Output lines parameters of the detected line in polar form function lines findline image 12 or canny image 2 1 0 00 1 00 12 1 9 I4 nonmaxsup I3 1 5 edgeimage hysthresh I4 0 20 0 15 theta 0 179 xp radon edgeimage theta max max R if maxv gt 25 i find R max max R else 93 lines return end foo ind sort R i u size i 1 k i ind 1 u y x ind2sub size R k t theta x pi 180 xp y lines cos t sin t r CX size image 2 2 1 cy size image 1 2 1 lines 3 lines 3 lines 1 cx lines 2 cy 9 99 99999999999999999999999999999999999999999999999999999999 9 findcircle m findcircle returns the coordinates of a circle in an image using the Hough transform and Canny edge detection to create the edge map Usage row col r findcircle image lrad
49. by companies governments military banks airports research laboratories border control for security purposes for allowing and limiting access to a particular information or area The government officials could also use this design for identifying and recording information of individuals and criminals Iris recognition technology can be used in places demanding high security Physical access based identification which includes anything requiring a password personal identification number or key for building access or the like could be replaced by this technology Unlike those physical methods of identification human iris cannot be stolen This technology addresses the problems of both password management and fraud D Design Constraints Good quality iris image can only be produced if the eye is approximately 3 to 4 cm away from the camera A solid red light from the proximity sensor would indicate that the human eye is within the range of 4 to 5 cm Every time an object is sensed the red LED generates a solid light and the camera captures an image of the object The system does not involve iris image processing and matching of individuals with eye disorders or contact lenses Since with these situations the iris image will be affected Also the system will only work properly when the captured image is an iris otherwise it will result to an error The speed of the system is limited by the computer specifications where the software is
50. c exposure control white balance and the likes The proximity sensor automates the camera The sensor decides on whether the target is positioned for capture The required input information is the iris image of a person for the iris recognition system database The image will be processed and analyzed by the built in algorithm in MATLAB The iris image will be stored in the database as stream of bits These bits will serve as the identification of the person who enrolled it and will also be used for template matching a process of finding the owner of the iris template by comparing every iris template in the database 125 A Statement of the Problem The existing Image Acquisition of the Iris Recognition System developed by Panganiban 2009 entitled CCD Camera with Near Infrared Illumination for Iris Recognition System recommends the enhancement of the device to improve the performance of the system The purpose of this innovation is to answer the following questions 3 Since quality image affects the critical success of iris image enrolment What camera should be used to get a better quality image to get a clear detail of the captured iris image 4 What are the additional components and changes needed and how can an installation of proximity sensor automate and enhance the precision of the camera and improve the matching rate of accuracy B Objectives of the Design The primary objective of this design is to automate and im
51. cept IRED Anode Pin Output Sinking Current Power Dissipation See Derating Curve Pp Junction Temperature Ty Ambient Temperature Tamb Range Operating Storage Temperature Tstg Range Soldering Temperature See Recommended Solder Profile see Figure 9 Average Output Current Teen DC Repetitive Pulsed Output 90 us ton lt 20 Current REDAnodeVoltage ue Voltage Receiver Data Output Vnxd 0 5 Veca V Voltage 05 Virtual Source Size Method d 25 2 8 mm 1 1 encircled energy Maximum Intensity for EN60825 1997 320 mW sr Class 1 Operation of unidirectional operation 825 1 or 60825 1 worst case test mode worst case IrDA FIR pulse pattern Document Number 82535 www vishay com Rev A1 0 13 Oct 00 3 11 119 TFDU5102 V Vishay Telefunken Electrical Characteristics Tamb 25 C Vec 3 0 V to 5 25 Vunless otherwise noted Typical values are for DESIGN AID ONLY not guaranteed nor subject to production testing Parameters TestConditions Pins Symbol Min Typ Max Unit Transceiver Supply Voltage Vcc 2 6 5 5 V Dynamic Supply Current Receive mode only In transmit mode add additional 85 mA typ for IRED current SD Low E 0 klx mA SD Low E 1 klx mA Standby Supply Current SD High Mode Floating T 25 E 0 klx 25 C E 1 klx
52. components are comprised of a 5 V power supply Near Infrared LEDs CMOS webcam proximity sensor Gizduino microcontroller and a_ personal computer And for the software the MS SQL 2005 Express Edition MATLAB 7 8 and Arduino compiler are used The design is assembled in a way that the subject s eye would be captured is aligned with the camera lens with respect to the time the sensor detects that the subject s face is on the specific range and sends signal to the microcontroller to automate the camera for capturing the iris image 28 Figure 3 6 5V Power Supply 5V Power Supply In the hardware part a 5 V 750 mA power supply is used to power up the NIR LEDs It is composed of a transformer rectifier capacitor and a regulator The transformer used is a step down transformer with a turn s ratio of approximately 18 33 in which it is able to produce a secondary AC voltage of 12 V from a primary AC voltage of 220 V The type of rectifier used is a bridge rectifier Four 4 001 diodes are used to build it so that it produces a full wave rectification in which the 12 Vac is converted to a 12 Vpc However this produces a varying DC output A 470 uF electrolytic capacitor is used to eliminate this and produce a small ripple voltage To produce a 5 V DC output a 5 V voltage regulator is used in this case LM7805 IC is used This also makes the voltage stable and accurate and a heat sink was attached to it in order to dissipate the h
53. d replace the webcam and NIR LEDs 3 Artificial Intelligence such as Fuzzy Logic can be applied to the system to improve the performance of the Iris recognition system 4 Embedding the Iris recognition system its hardware and software into one device can be done to have the speed of the system independent on the speed of the computer used and could also be portable 46 REFERENCES Addison P 2002 The Illustrated Wavelet Transform Handbook Institute of Physics Bradley J Brislawn C and Hopper T 1993 The FBI Wavelet Scalar Quantization Standard for Gray scale Fingerprint Image Compression Tech Report LA UR 93 1659 Los Alamos Nat l Lab Los Alamos N M Boles W W and Boashash B A 1998 A human identification technique using images of the iris and wavelet transform IEEE trans on signal processing vol 46 issue 4 Canny J 1986 A Computational Approach To Edge Detection IEEE Trans Pattern Analysis and Machine Intelligence 8 679 714 Cohn J 2006 Keeping an Eye on School Security The Iris Recognition Project in New Jersey Schools NIJ Journal no 254 Huifang H and Guangshu H 2005 Iris recognition based on adjustable scale wavelet transform Proceedings of the 2005 IEEE 47 Kong W and Zhang D 2001 Accurate iris segmentation based on novel reflection and eyelash detection model Proceedings of 2001 International Symposium on Intelligent Multimedia Vi
54. d Image Table 4 4 Iris Image Quality Assessment In Table 4 4 it can be observed that the improved design really showed promising results The design produced a clear and bright image even though the image was magnified in the test The magnification testing was made by zooming in the images Also there was no noise in the iris image Table 4 5 Enrolled Captured Iris Images DATASETS In Table 4 5 the iris images that were captured and enrolled into the Iris Recognition System are displayed These images undergone image processing as discussed in the previous chapter to have its iris template be produced The iris templates were encoded using the Haar mother wavelet because according to Engr Panganiban s work it resulted with the best values of Hamming distance after every iris template were compared The Inter class comparisons of Haar wavelet at Level 4 vertical coefficient is shown on Table 4 6 132 As seen on the table the maximum HD value is 0 1538 and the minimum is 0 1060 A zero value indicates that the iris templates are perfectly matching each other e ER EE ERR EE Id 0127 04334 0 1081 HRS 0 1331 01518 1351 01277 0 1414 3 01331 Oat 11351 0 1268 0 1081 0 1247 4 01268 0 1518 0 1268 01247 11377 0 1206 0 143 E OTIS 8138 E207 1086 0172 058 1448 OST 010 6 068 3 08 0 27 61372 099 0 1289 0382 0577 0 1268 1045 E
55. d or a return signal The proximity sensor automates the camera by deciding on whether the target is positioned for capture Iris Image Acquisition Image acquisition depends highly on the image quality According to Dong et al 2008 the average iris diameter is averagely 10 millimeters and the required pixel number in iris diameter is normally more than 150 pixels in iris image acquisition systems The International standard regulates that 200 pixels is of good quality 150 200 is acceptable quality and 100 150 is marginal quality The iris image with a smaller pixel is considered as of a better quality image and a bigger pixel as of less quality image In Panganiban s study 2010 it was mentioned that Phinney and Jelinek have claimed that near infrared illumination is safe to the human eye Derwent Infrared Illuminators supported the safeness of near infrared illumination to the eye Studies showed that filtered infrared is approximately 100 times less hazardous than the visible light 14 Iris Recognition System and Principles Libor Masek s proposed algorithm showed an automatic segmentation algorithm which localise the iris region from an eye image and isolate eyelid eyelash and reflection areas The circular Hough transform which localised the iris and pupil regions was used for the automatic segmentation and the linear Hough transform was used for localising occluding eyelids Thresholding was performed for
56. deo and Speech Processing Hong Kong Makram Nabti and Bouridane 2007 An effective iris recognition system based on wavelet maxima and Gabor filter bank IEEE trans on iris recognition Masek L 2003 Recognition of Human Iris Patterns for Biometric Identification Narote et al 2007 An iris recognition based on dual tree complex wavelet transform IEEE trans on iris recognition Panganiban A 2009 CCD Camera with Near Infrared Illumination for Iris Recognition System 2010 Implementation of Wavelet Algorithm for Iris Recognition System 48 APPENDIX A Operation e Manual I System Requirements CPU Intel Core i7 Memory 4 00 GB Operating System Windows 7 Software MATLAB R2009a II Installation Procedure MATLAB R2009a installation Recommended 1 1 Load the MATLAB R2009a installer it should automatically start the installation program whereby the first splash screen could be seen 1 2 Agree to the Mathworks license and then press Next 1 3 Choose the Typical installation and then press Next 1 4 Choose the location of the installation and then press Next 1 5 If the location doesn t exist you will be prompted to create it and MATLAB will ask you for the location on where the files will be installed 1 6 Confirm the installation settings by pressing Install 17 MATLAB will now install this may take several minutes 49 1 8 Close to the end of the installation you will b
57. deployed The recommended system requirements for the software application is a multi core 2 20 GHz or higher for the CPU a 4 00 GB or higher for the RAM and Windows 7 for the operating system REVIEW OF RELATED LITERATURE AND STUDIES Iris Recognition Technology Biometrics became popular in security applications due to its personal identification and verification based on the physiological and behavioural characteristics of the subject Among the existing biometric technologies it is iris recognition that is considered promising which uses the apparent pattern of the human iris Panganiban 2010 The iris is a muscle within the eye that regulates the size of the pupil which controls the amount of light that enters the eye It is the colored portion of the eye with coloring based on the amount of melatonin pigment within the muscle The coloration and structure of the iris is genetically linked but the details of the patterns are not National Science and Technology Council 2006 Retina Figure 2 1 Iris Diagram 126 Irises contain approximately 266 distinctive characteristics about 173 of which are used to create the iris template and serves as a basis for biometric identification of individuals Iris patterns possess high inter class dependency and low intra class dependency Daugman 1993 Image Quality According to Kalka et al the performance of the iris recognition system particularly recognition and segmenta
58. dering Information a aoa acc 55 i LM555CMMX 3 5k Units Tape and Reel SFin DE EECHER www national com 2 110 Absolute Maximum Ratings note 2 If Military Aerospace specified devices are required please contact the National Semiconductor Sales Office Distributors for availability and specifications Supply Voltage 18V Power Dissipation Note 3 LM555CM LM555CN 1180 mw LM555CMM 613 mW Operating Temperature Ranges LM555C 0 C to 70 C Storage Temperature Range 65 C to 150 C Electrical Characteristics notes 1 2 25 C Voc 5V to 15V unless othewise specified Parameter Conditions Supply Voltage Supply Current Voc 5 Vcc 15V Low State Note 4 Timing Error Monostable Initial Accuracy Drift with Temperature Ra 1k to 100kQ 0 1pF Note 5 Accuracy over Temperature Drift with Supply Timing Error Astable Initial Accuracy Drift with Temperature Ra Rg 1k to 100kQ 0 1pF Note 5 Accuracy over Temperature Drift with Supply Threshold Voltage Trigger Voltage Trigger Current Reset Current Threshold Current Note 6 Control Voltage Level Pin 7 Leakage Output High Pin 7 Sat Note 7 Output Low Voc 15V 5 15mA Output Low Voc 4 5V 4 5mA Soldering Information Dual In Line Package Soldering 10 Seconds Small Outline Packages SOIC and MSOP Vapor Phase 60 Seconds Infrared 15 Seconds
59. design IMPACT OF THE DESIGN The design is an Automated Iris Recognition System it is generally made for improving its image acquisition This would capture an image of the iris Nowadays this biometric technology shows an increasing promise on the security system for it studies the unchanging measurable biological characteristics that are unique to each individual Among the existing biometric devices and scanners available today it is generally conceded that iris recognition is the most accurate The design can be used as a prototype which can be implemented by companies governments military banks airports research laboratories border control for security purposes for allowing and limiting access to a particular information or area The government officials could also use this design for identifying and recording information of individuals and criminals Iris recognition technology can be used in places demanding high security Physical access based identification which includes anything requiring a password personal identification number or key for building access or the like could be replaced by this technology Unlike those physical methods of identification human iris cannot be stolen This technology addresses the problems of both password management and fraud DESIGN CONSTRAINTS Good quality iris image can only be produced if the eye is approximately 3 to 4 cm away from the camera A solid red light from the proximity sen
60. distance inspection Else if it s not to be enrolled then the system just goes back to the distance inspection IrisDataBankDesign Column Key Allow Null PK No LEES varchar 50 Yes IrisTemplate Yes Figure 3 4 Relational Model The template bits are stored in a database using Microsoft SQL 2005 Express edition In Fig 3 4 the IrisId field is set to auto increment by 1 and the primary key While the IrisPath and IrisTemplate depends on the output of the system which is inserted to the database C Prototype Development Quantity Material Description 1 pe 5 V 750 mA Powers up the NIR Power Supply LEDs 12 pcs NIR LEDs Illuminates the iris 1 pc Proximity Sensor Senses if the iris is within the detecting range 1 pc Gizduino Implements the Microcontroller designed program 1 pc Webcam Captures the iris image 130 IV TESTING PRESENTATION AND INTERPRETATION OF DATA Automated CMOS Camera for iris recognition through proximity sensor focus on its objective of improving an existing image acquisition of the iris recognition system developed by Engr Panganiban and the design s automation In this chapter the researchers conduct experiments to identify whether the hardware and software design meet the criteria for an effective iris recognition system Several observations and assessments
61. e an arduino variable end check pin errstrzarduino checknum pin analog input pin number 0 5 if isempty errstr error errstr end check a aser for validity errstr arduino checkser a aser valid if isempty errstr error errstr end 00 00 00 o 00 o 0 0 o o 0 0 0000 00 Din D n Din Die O Dn Din O PERFORM ANALOG INPUT 000 000 0 0 00 0 0 000 0 00 Din D n 00 D n 0 0 0000 00 Din 00 Din 0000 00000000 if strcempi get a aser handle demo mode average analog input delay pause 0 0267 69 output a random value between 0 and 1023 val round 1023 rand else check a aser for openness errstr arduino checkser a aser open if isempty errstr error errstr end send mode and pin fwrite a aser 51 97 pin uchar get value val fscanf a aser 9od end end 96 analogread function analog write function analogWrite a pin val 9o a analogWrite pin val Performs analog output on a given arduino pin 9o The first argument before the function name a is the arduino object 9o The first argument pin is the number of the DIGITAL pin where the analog PWM output needs to be performed Allowed pins for AO are 3 5 6 9 10 11 9o The second argument val is the value from 0 to 255 for the level of analog output Note that the digital pins from O to 13 are located on the upper right part of the board Examples
62. e asked if you want to set up some file associations Choose Yes to All 1 9 After the installation has completed you will be asked for the serial key for the software license Enter the serial key and press Next 1 10 MATLAB will initially make an internet connection to Mathworks Answer Yes when asked if you are a student Then press Next 1 11 Enter the serial key and your email address Then press Next 1 12 Continue with the rest of the registration process until the installation is complete Arduino Compiler installation For Windows 2 1 Get an Arduino board and connect it to your computer with a USB cable 2 2 Download the Arduino environment its official website http arduino cc en Main Software 2 3 Install the drivers 2 3 1 Wait for Windows to begin its driver installation process After a few moments the process will fail despite its best efforts 2 3 2 Click on the Start Menu and open up the Control Panel 50 2 3 3 While in the Control panel navigate to System and Security Next click on System Once the System window is up open the Device Manager 2 3 4 Look under Ports COM amp LPT There should be an open port named Arduino UNO COMxx 2 3 5 Right click on the Arduino UNO COMxx port and choose the Update Driver Software option 2 3 6 Next choose the Browse my computer for Driver software option 2 3 7 Finally navigate to and select the UNO s d
63. eat produced by the circuit 29 Figure 3 7 NIR LED NIR LEDs For the NIR LEDs a series parallel circuit connection is used Considering the current each LED has a forward current of 100 mA and the power supply could only produce 750 mA output Also taking in to account for the voltage the typical forward voltage of each LED which are used is 1 5 V and the power supply can only produce a 5 V output Because of these current and voltage settings only up to 7 parallel set of LEDs and each set contains 3 IR LEDs respectively A resistor should be used in order to protect the LEDs from burning In the computation 5 Ohms resistor is calculated This value can protect the LEDs from burning because it can control the current below 100mA Using the next lower resistor value would destroy the LEDs 30 Figure 3 8 Proximity Sensor Proximity Sensor The proximity sensor used is an infrared proximity collision sensor It is produced and manufactured by E Gizmo Electronics and Robotics Shop It has two wires for input and one for output The input wires which are colored red and green are for the 5V supply and the ground connection respectively For its power it uses the Gizduino microcontroller board for its 5V source since this microcontroller could deliver such a voltage output It uses a TFDU6103 IrDa transceiver see datasheets for info There are two of it in the sensor one serves as the receiver and the other as the transmitter
64. emote controls capability Communications paging decoders Bandwidth adjustable from 0 to 14 Jepooe euo OLOSINT Z9SINT Connection Diagrams Metal Can Package Dual In Line and Small Outline Packages OUTPUT OUTPUT OUTPUT FILTER FILTER LOOP FILTER CAPACITOR TIMING INPUT TIMING RESISTOR CAPACITOR TIMING RESISTOR 00697 501 Top View Order Number LM567H or LM567CH See NS Package Number 08 00697 502 Top View Order Number LM567CM See NS Package Number Order Number LM567CN See NS Package Number 08 2004 National Semiconductor Corporation DS006975 www national com 113 LM567 LM567C Absolute Maximum Ratings note 1 If Military Aerospace specified devices are required please contact the National Semiconductor Sales Office Distributors for availability and specifications 9v 1100 mw 15V 10V V4 0 5V 65 C to 150 C Supply Voltage Pin Power Dissipation Note 2 Vs Vs Vs Storage Temperature Range Operating Temperature Range Electrical Characteristics AC Test Circuit 25 C 5V Parameters Conditions Power Supply Voltage Range Power Supply Current Quiescent Power Supply Current Activated Input Resistance Smallest Detectable Input Voltage Largest No Output Input Voltage L 100 mA f fo 100 mA fi fs Largest Simultaneous Outband Signal to Inband Signal Ratio Minimum Input Signal to Wideband Noise Ratio Largest Detection Bandw
65. emplate1s 2 xor template1s templateb bitsdiff sum sum C 1 if totalbits HD NaN else 1 bitsdiff totalbits 106 if hdi lt HD isnan HD HD hd1 end end end 9 99999999999999999999999999999999999999999 999999999999 999999 9 encode m function output encode image image double image C S wavedec2 image 4 haar cH2 cV2 cD2 detcoef2 all C S 1 cA1 cH1 cV1 cD1 swt2 image 1 haar index2 1 C 1 cV2 cD2 2 row col size C col2 col 2 template zeros 1 col2 for index 1 col if C index gt 0 5 template index2 1 index2 index2 1 template index2 1 elseif C index 0 5 amp C index gt 0 template index2 1 index2 index2 1 template index2 0 elseif C index gt 0 amp C index gt 0 5 template index2 0 index2 index2 1 template index2 1 elseif C index lt 0 5 template index2 0 index2 index2 1 template index2 0 else index2 index2 1 end index2 index2 1 end output template 107 APPENDIX D Data Sheets List of Data Sheets 1 LM555 Timer 2 LM567 Tone Decoder 3 IR LED GaAIAs Infrared Emitters 880nm SFH485 4 IrDA Fast Infrared Transceiver TFDU5102 5 LM7808 Voltage Regulator 108 National Semiconductor LM555 Timer General Description The LM555 is a highly stable device for generating accurate time delays or osc
66. ermal effects and aerosols Lost sharpness can be restored by sharpening but sharpening has limits Over sharpening can degrade image quality by causing halos to appear near contrast boundaries Dynamic range or exposure range is the range of light levels a camera can capture usually measured in f stops Exposure Value or zones It is closely related to noise high noise implies low dynamic range Contrast also known as gamma is the slope of the tone reproduction curve in a log log space High contrast usually involves loss of dynamic range loss of detail or clipping in highlights or shadows Motion blur is the apparent streaking of rapidly moving objects in a still image or a sequence of images This results when the image being captured changes during the grabbing of a single frame either due to rapid movement or long exposure Pixel resolution is often used for a pixel count in digital imaging An image of N pixels high by M pixels wide can have any resolution less than N lines per picture height or N TV lines But when the pixel counts are referred to as resolution the convention is to describe the pixel resolution with the set of two positive integer numbers where the first number is the number of pixel columns width and the second is the number of pixel rows height for example as 640 by 480 Another popular convention is to cite resolution as the total number of pixels in the image typically given as number of mega
67. ex n will be n rows 1 n 1 n rows 1 n rowSs n n rows n rows 1 n 1 n rows i O 1 1 rows 1 rows rows 1 rows 1 rows rows 1 while stp 0 While the stack is not empty v stack stp Pop next index off the stack stp stp 1 gt amp v lt Prevent us from generating illegal indices Now look at surrounding pixels to see if they should be pushed onto the stack to be processed as well index Calculate indices of points around this pixel for 1 8 91 ind index l if bw ind gt T2 if value gt T2 stp stp 1 push index onto the stack stack stp ind bw ind 1 mark this as an edge point end end end end bw bw 1 Finally zero out anything that was not an edge bw reshape bw rows cols and reshape the image 999999999999999999999999999999999999999999999999999999999999 houghcircle m houghcircle takes an edge map image and performs the Hough transform for finding circles in the image Usage h houghcircle edgeim rmin rmax Arguments edgeim the edge map image to be transformed rmin rmax the minimum and maximum radius values of circles to search for Output h the Hough transform function h houghcircle edgeim rmin rmax rows cols size edgeim nradii rmax rmin 1 h zeros rows cols nradii find edgeim 0 for each edge point dr
68. f 5 V is the voltage drop of 1 5 V and an Ig is a current of 100 mA The formula would produce a resistance of 35 ohms But considering that we are to connect in parallel four rows of 3 NIR LEDs in series the resulting resistance value R connected in series with the 3 NIR LEDs on each row would be 5 ohms The proximity sensor detects the presence of nearby objects without any physical contact This type of sensor emits a beam of electromagnetic radiation such as infrared and looks for changes in the field or a return signal This gives the appropriate signal to the image capturing software when the subject is in the right position for iris image acquisition The Gizduino microcontroller is a clone of Arduino microcontroller made by the company E Gizmo It has a built in ATMEGA microcontroller and PL2303 USB to RS 232 Bridge Controller B Software Development Initialize camera and microcontroller settings gizduinoPort No Yes xm RE gizduinoPort digitalRead 2 8 0 a T Yes capture image iris image processing match template with the irises stored in the database display Authenticated S Ho display Not Authenticated MM No a enroll the iris to EIS database DES Yes insert iris template and path to database euo Figure 3 3 System Flo
69. f 5 After that a biometric template is produced Similar to 22 Engr Panganiban s work the wavelet transform is used to extract the discriminating information in an iris pattern Only one mother wavelet is used which is the Haar because it produced the highest CRR according to Engr Panganiban s thesis The template is encoded using the patterns that yielded during the wavelet decomposition Then the algorithm will check if the template matches another template stored in the database by using its binary form to compute for the hamming distance of the two templates This is done by using the XOR operation A template can also be added to the database by using MS SQL queries Figure 3 3 describes the schematic diagram of the hardware components used in the design project The Near Infrared LEDs are powered by the 5V power supply The power supply is composed of a transformer rectifier capacitor and a regulator The transformer converts electricity from one voltage to another with minimal loss of power It only works with an alternating current because it requires a changing magnetic field to be created in its core Since 5 V supply is only needed step down transformer was used The voltage source was reduced to 12 V AC The rectifier converts an AC waveform into a DC waveform It uses diodes which allows current to flow through it in one direction The Full Wave Rectifier converted 12 V AC to 12 V DC The electrolytic capacitor smoothen the ri
70. f PAL 512 528 512x492 Manual focus according Manual Focus 2cm to Focus Range bria rakna infinity according to user p requirement Table 4 3 Camera Specifications Specifications Image Sensor Our group replaced Eng r Panganiban s CCD Camera with a CMOS Camera The camera must possess excellent imaging performance in order to produce accurate results In a CCD Charge Couple Device sensor every pixel s charge 1s transferred through a very limited number of output nodes to be converted to voltage buffered and sent off chip as an analog signal All of the pixel can be devoted to light capture and the uniformity of the output is high In a CMOS Complementary Metal Oxide Semiconductor sensor each pixel has its own charge to voltage conversion and the sensor often includes amplifiers noise correction and digitalization circuits so that the chip outputs digital bits With these the design complexity increases and the area available for light capture decreases The uniformity is lower because each pixel is doing its own conversion Also both cameras that were used were manual focus for the user to adjust it to their system s requirements Figure 4 1 Selected Iris Images from Engr Panganiban s system 131 Figure 4 2 Selected Iris Images from the Current System Common Quality Metrics Figure 4 2 Blur Motion Blurred Image Noise in the Iris Image Without Noise Brightness Dark Magnification Blurre
71. ge center as well as the sensor pixel count and anti aliasing filter In the field sharpness is affected by camera shake focus accuracy and atmospheric disturbances like thermal effects and aerosols Lost sharpness can be restored by sharpening but sharpening has limits Over sharpening can degrade image quality by causing halos to appear near contrast boundaries Dynamic range or exposure range is the range of light levels a camera can capture usually measured in f stops Exposure Value or zones It is closely related to noise high noise implies low dynamic range Contrast also known as gamma is the slope of the tone reproduction curve in a log log space High contrast usually involves loss of dynamic range loss of detail or clipping in highlights or shadows Motion bluris the apparent streaking of rapidly moving objects in a still image or a sequence of images This results when the image being captured changes during the grabbing of a single frame either due to rapid movement or long exposure Pixel resolution is often used for a pixel count in digital imaging An image of N pixels high by M pixels wide can have any resolution less than N lines per 12 picture height or N TV lines But when the pixel counts are referred to as resolution the convention is to describe the pixel resolution with the set of two positive integer numbers where the first number is the number of pixel columns width and the second is the numbe
72. ghly on the image quality According to Dong et al 2008 the average iris diameter is averagely 10 millimeters and the required pixel number in iris diameter is normally more than 150 pixels in iris image acquisition systems The International standard regulates that 200 pixels is of good quality 150 200 is acceptable quality and 100 150 is marginal quality The iris image with a smaller pixel is considered as of a better quality image and a bigger pixel as of less quality image In Panganiban s study 2010 it was mentioned that Phinney and Jelinek have claimed that near infrared illumination is safe to the human eye Derwent Infrared Illuminators supported the safeness of near infrared illumination to the eye Studies showed that filtered infrared is approximately 100 times less hazardous than the visible light 127 Iris Recognition System and Principles Libor Masek s proposed algorithm showed an automatic segmentation algorithm which localise the iris region from an eye image and isolate eyelid eyelash and reflection areas The circular Hough transform which localised the iris and pupil regions was used for the automatic segmentation and the linear Hough transform was used for localising occluding eyelids Thresholding was performed for the isolation of the eyelashes and reflections The segmented iris region was normalised by implementing Daugman s rubber sheet model The iris is modelled as a flexible rubber
73. he main intention of this design is to implement it for security function since it is very useful to this field having a fact that an iris of a human is the most unique even for a person the left iris has different pattern of wavelets compared to that of the right iris of the same person This design includes an automated CMOS camera and proximity sensor for iris recognition system A CMOS camera or complementary metal oxide semiconductor camera has a CMOS image sensor in which has an ability to integrate a number of processing and control functions These features include timing logic exposure control white balance and the likes The proximity sensor automates the camera The sensor decides on whether the target is positioned for capture The required input information is the iris image of a person for the iris recognition system database The image will be processed and analyzed by the built in algorithm in MATLAB The iris image will be stored in the database as stream of bits These bits will serve as the identification of the person who enrolled it and will also be used for template matching a process of finding the owner of the iris template by comparing every iris template in the database STATEMENT OF THE PROBLEM The existing Image Acquisition of the Iris Recognition System developed by Panganiban 2009 entitled CCD Camera with Near Infrared Illumination for Iris Recognition System recommends the enhancement of the device to
74. idth Largest Detection Bandwidth Skew Largest Detection Bandwidth Variation with Temperature Largest Detection Bandwidth Variation with Supply Voltage Highest Center Frequency Center Frequency Stability 4 75 5 75V 20k B 140 kHz 4 75 6 75V 0 lt T lt 70 55 lt lt 125 Center Frequency Shift with Supply 6 Voltage Fastest ON OFF Cycling Rate Output Leakage Current Output Saturation Voltage lt ZS N N Du aa S Ss a lt 2 a lt e 25 mV lg 30 mA e 25 mV lg 100 mA Output Fall Time Output Rise Time S 2a 3 3 5 5 5 lt o 5 5 N ol oo LM567H LM567CH LM567CM LM567CN Soldering Information 55 C to 125 C 0 C to 70 C Dual In Line Package Soldering 10 sec 260 C Small Outline Package Vapor Phase 60 sec 215 C Infrared 15 sec 220 C See AN 450 Surface Mounting Methods and Their Effect on Product Reliability for other methods of soldering surface mount devices LM567C LM567CM yp a ojo 4 A a E H A 49 7 Oo o 22 lt H Nis nl gt EI a oo a H S H a gt oj NN m A o Aaja oo a d 3 zx gd Oo 3 Oo i 150 i E ag o o o Note 1 Absolute Maximum Ratings indicate limits beyond which damage to the device may occur Operating Ratings indicate co
75. illation Additional terminals are provided for triggering or resetting if desired In the time delay mode of operation the time is precisely controlled by one external resistor and capacitor For astable operation as an oscillator the free running frequency and duty cycle are accurately controlled with two external resistors and one capacitor The circuit may be triggered and reset on falling waveforms and the output circuit can source or sink up to 200mA or drive TTL circuits Schematic Diagram 8 Vee O 6 ir THRESHOLD P CONTROL 5 2 3 TRIGGER 7 DISCHARGE 2006 National Semiconductor Corporation 05007851 July 2006 99911071 Features Direct replacement for 5 555 555 Timing from microseconds through hours Operates in both astable and monostable modes Adjustable duty cycle Output can source or sink 200 mA Output and supply TTL compatible Temperature stability better than 0 005 per C Normally on and normally off output Available in 8 pin MSOP package Applications Precision timing Pulse generation Sequential timing Time delay generation Pulse width modulation Pulse position modulation Linear ramp generator gt 00785101 www national com 109 LM555 Connection Diagram Dual In Line Small Outline and Molded Mini Small Outline Packages Mee TRIGGER DISCHARGE OUTPUT THRESHOLD CONTROL VOLTAGE 00785103 Top View Or
76. improve the performance of the system The purpose of this innovation is to answer the following questions 1 Since quality image affects the critical success of iris image enrolment What camera should be used to get a better quality image to get a clear detail of the captured iris image 2 What are the additional components and changes needed and how an installation of proximity sensor automate and enhance the precision of the camera and improve the matching rate of accuracy OBJECTIVES OF THE DESIGN The primary objective of this design is to automate and improve the existing Image Acquisition of the Iris Recognition System by Engr Panganiban Specifically for the success of this design the following objectives must be met 1 The Camera to be used with the help of the NIR LEDs must be able to produce an image of the subject s iris 2 NIR LEDs must be located where it would give enough IR light to the subject s iris This would help make the iris more visible to the camera and to the image for capture 3 The Proximity sensor should be installed to the system which would detect whether the person is at the correct distance and position before capturing the subject s iris 4 The system must be able to recognize the difference between the irises to be processed through Hamming distance values and show the separation of classes through degree of freedom DoF 5 The system must have a DoF improvement on Engr Panganiban s
77. ion algorithm for analysis 19 Hardware Development RIS SEGMENTATION i connected to HUMAN SUBJECT 1 Gizduino Microcontroller connected to NORMALISATION COMPUTER WITH MATLAB SOFTWARE tb TEMPLATE ENCODING STORE IF TO ENROLL DATABASE 1100101010101010101010101010111111 C 9 MATCH 1010101011110000111010101010101010 lt AUTHORIZED IRIS TEMPLATE Figure 3 1 Conceptual Framework 20 Automation Proximity Sensor Human Subject Human Face Microcontroller Image Acquisition Software Subject Human Eye NIR LEDs Iris Recognition Algorithm er o 2365628 Iris Segmentation V Normalisation Template Encoding EM oO Template Matching Iris Template Database Enrollment Figure 3 2 Block Diagram Figure 3 2 represents the block diagram that was implemented to attain the goals of the design The automation part is composed of the proximity sensor the microcontroller and the image acquisition software This automation block as its name implies automates the capturing of the webcam through the use of the sensor that is connected to the microcontroller in which is handled by the image 21 acquisition software The proximity sensor senses objects within 10cmrange from its transceiver The microcontroller used is the Gizduino microcontroller manufactured and produced by E
78. is double y_iris r_iris double r_iris x_pupil double x_pupil y pupil double y_pupil r_pupil double r_pupil calculate displacement of pupil center from the iris center OX X_pupil x_iris oy y_pupil y_iris if ox lt 0 sgn 1 elseif ox gt 0 sgn 1 end if ox 0 amp amp oy gt 0 sgn 1 end r double r theta double theta a ones 1 angledivisions 1 2 2 need to do something for ox 0 if ox phi pi 2 else 102 phi atan oy ox end b sgn cos pi phi theta calculate radius around the iris as a function of the angle sqrt a b sqrt a b 2 a iris 2 r r r pupil rmat ones 1 radiuspixels r rmat rmat ones angledivisions 1 1 0 1 radiuspixels 1 1 rmat rmat r_pupil exclude values at the boundary of the pupil iris border and the iris scelra border as these may not correspond to areas in the iris region and will introduce noise ie don t take the outside rings as iris data rmat rmat 2 radiuspixels 1 calculate cartesian location of each data point around the circular iris region xcosmat ones radiuspixels 2 1 cos theta xsinmat ones radiuspixels 2 1 sin theta rmat xcosmat yo rmat xsinmat XO yo X_pupil xo y pupil yo extract intensity values into the normalised polar representation through interpolation x y
79. is Image 39 10 DATASETS In Table 4 5 the iris images that were captured and enrolled into the Iris Recognition System are displayed These images undergone image processing as discussed in the previous chapter to have its iris template be produced The iris templates were encoded using the Haar mother wavelet because according to Engr Panganiban s work it resulted with the best values of Hamming distance after every iris template were compared The Inter class comparisons of Haar wavelet at Level 4 vertical coefficient is shown on Table 4 6 As seen on the 40 table the maximum HD value is 0 1538 and the minimum is 0 1060 A zero value indicates that the iris templates are perfectly matching each other Table 4 6 Inter class comparisons of Haar wavelet at Level 4 vertical coefficient Iris 1 2 3 4 5 6 7 8 9 10 Id 0 0000 0 1331 0 1331 0 1268 0 1060 0 1268 0 1227 0 1331 0 1081 0 1206 0 1331 0 0000 0 1331 0 1518 0 1351 0 1268 0 1227 0 1372 0 1372 0 1414 0 1331 0 1331 0 0000 0 1268 0 1351 0 1227 0 1268 0 1081 0 1247 0 1372 0 1268 0 1518 0 1268 0 0000 0 1247 0 1372 0 1206 0 1143 0 1227 0 1060 0 1060 0 1351 0 1351 0 1247 0 0000 0 1123 0 1538 0 1435 0 1351 0 1310 0 1268 0 1268 0 1227 0 1372 0 1123 0 0000 0 1289 0 1393 0 0977 0 1
80. is handled by the image acquisition software An additional feature of this design is the real time processing of image Once the iris was captured the software would automatically perform iris segmentation normalization template encoding and template matching It would then display if your iris is authenticated enrolled or not In matching the templates when the Hamming distance value is greater than or equal to 0 1060 the iris templates do not match but when the HD value is less than 0 1060 the iris template are from the same individual In comparing the accuracy of the iris templates in our design the Degrees of Freedom DoF was computed The computed DoF of our design is 80 which is higher than that of Engr Panganiban s work Keywords biometrics iris recognition hamming distance wavelet real time image processing viii Chapter 1 DESIGN BACKGROUND AND INTRODUCTION BACKGROUND Biometrics is becoming popular nowadays due to its very useful security applications The technology uses the unique characteristics of an individual in an electronic system for authentication Biometric technologies used as a form of identity access management and access control are becoming the foundation of an extensive array of highly secure identification and personal verification solutions There are several of applications for biometrics which include civil identity infrastructure protection government public safety and the like As for t
81. isible function irisrecognition_OpeningFcn hObject eventdata handles varargin setup webcam vidobj videoinput winvideo 1 YUY2_640X480 set handles statusLbl String Connecting to camera vidobj videoinput winvideo 3 RGB24_640X480 axes handles CameraAxes videoRes get vidobj VideoResolution numberOfBands get vidobj NumberOfBands fprintf 1 Video resolution d wide by d tall by d color videoRes 1 videoRes 2 numberOfBands handleToImage zeros videoRes 2 videoRes 1 numberOfBands uint8 set vidobj ReturnedColorSpace RGB uint8 img set handles statusLbl String Camera ready preview vidobj handleToImage end setup webcam set arduino set handles statusLbl String Connecting to Gizduino gizduinoPort arduino COM4 set handles statusLbl String Gizduino ready gizduinoPort pinMode 8 input Yowhere the output of the proximity sensor goes gizduinoPort pinMode 11 output made 5V supply 11 for the V of the proximity sensor gizduinoPort digitalWrite 11 1 9ooutput high signal on 11 5V end set arduino while gizduinoPort 0 nakaconnect ang microcontroller myWait 5 for n seconds if gizduinoPort digitalRead 8 0 kapag may harang set handles statusLbl String Capturing iris image 77 frame getsnapshot vidobj imwrite
82. ius uradius scaling sigma hithres lowthres vert horz Arguments image the image in which to find circles radius lower radius to search for 9o uradius upper radius to search for scaling scaling factor for speeding up the Hough transform sigma amount of Gaussian smoothing to apply for creating edge map 9o hithres threshold for creating edge map 9o lowthres threshold for connected edges vert vertical edge contribution 0 1 9o horz horizontal edge contribution 0 1 Output 9o circleiris centre coordinates and radius of the detected iris boundary 94 circlepupil centre coordinates and radius of the detected pupil boundary imagewithnoise original eye image but with location of noise marked with NaN values function row col findcircle image lradius uradius scaling sigma hithres lowthres vert horz Iradsc round lradius scaling uradsc round uradius scaling rd round uradius scaling Iradius scaling generate the edge image 12 or canny image sigma scaling vert horz 1 9 to 1 5 for gamma adjgamma L2 1 8 I4 nonmaxsup I3 or 1 5 edgeimage hysthresh I4 hithres lowthres perform the circular Hough transform h houghcircle edgeimage lradsc uradsc maxtotal 0 find the maximum in the Hough space and hence the parameters of the circle for i 1 rd layer 1 maxlayer max
83. k a aser for openness errstr arduino checkser a aser open if isempty errstr error errstr end 9o send mode pin and value fwrite a aser 50 97 pin 48 val uchar end end digitalwrite analog read function val analogRead a pin val a analogRead pin Performs analog input on a given arduino pin The first argument before the function name a is the arduino object The second argument pin is the number of the analog input pin 0 to 5 where the analog input needs to be performed The returned value val ranges from 0 to 1023 with 0 corresponding to an input voltage of 0 volts 68 analog does and 1023 to a value of 5 volts Therefore the resolution is 0049 volts 4 9 mV per unit Note that the analog input pins 0 to 5 are also known as digital pins from 14 to 19 and are located on the lower right corner of the board Specifically analog input pin 0 corresponds to digital pin 14 and input pin 5 corresponds to digital pin 19 Performing analog input not affect the digital state high low digital input of the pin Example val a analogRead 0 reads analog input pin 0 9 00 00 90 909 00 909 909 909 909 909 90 9 ARGUMENT CHECKING o check nargin if narginv 2 error Function must have the pin argument end first argument must be the arduino variable if isa a arduino error The first argument must b
84. k if we are already connected if isa a aser serial amp amp isvalid a aser amp amp strcmpi get a aser Status open disp It looks like Arduino is already connected to port comPort disp Delete the object to force disconnection disp before attempting a connection to a different port 58 return end check whether serial port is currently used by MATLAB if isempty instrfind Port comPort disp The port comPort is already used by MATLAB disp If you are sure that Arduino is connected to comPort disp then delete the object to disconnect and execute disp delete instrfind Port comPort disp to delete the port before attempting another connection error Port comPort already used by MATLAB end define serial object a aser serial comPort connection if strcmpi get a aser Port DEMO handle demo mode fprintf 1 Demo mode connection for i 1 4 fprintf 1 pause 1 end fprintf 1 n pause 1 chk is 1 or 2 depending on the script running on the board chk round i rand else actual connection open port try fopen a aser catch ME disp ME message delete a error Could not open port comPort end it takes several seconds before any operation could be attempted 59 fprintf 1 Attempting connection for i 1 4 fprintf 1 pause 1 end fprintf 1 n query script type
85. lowed num form right error string if numel allowed 1 errstr Unallowed value for description the value must be exactly num2str allowed 1 elseif numel allowed 22 errstr Unallowed value for description the value must be either num2str allowed 1 or num2str allowed 2 elseif max diff allowed 1 errstr Unallowed value for description the value must be an integer going from num2str allowed 1 to num2str allowed end else errstr Unallowed value for description the value must be one of the following mat2str allowed end end end checknum function errstr checkstr str description allowed 9o errstr arduino checkstr str description allowed Checks string argument This function checks the first argument str described in the string 9o given as a second argument to make sure that it is a string and that its first character is equal to one of the entries in the cell of 73 allowed characters given as a third argument If the check is successful then the returned argument is empty otherwise it is a string specifying the type of error preliminary check nargin if narginv 3 error checkstr needs 3 arguments please read the help end preliminary check description if isempty description ischar description error checknum second argument must be a string end preliminary check allowed if iscell allowed numel allowed lt
86. lue the comparison between the relative values of Hamming distances can lead to correct recognition The determination of identity in her study was based on both the threshold value and on a comparison of HD values The test metrics proved that her proposed algorithm has a high recognition rate Biometric Test Metrics Ives et al 2005 determined the consequences of compression through the analysing the compression rate Also each pair of curves False Rejection Rate FRR and False Accept Rate FAR represents the comparison of each compressed database against the original database An original versus original comparison is included as a baseline The compression ratio increases the FAR curve remains virtually unchanged while the FRR curves move further to the right which causes an increased Equal Error Rate EER where FAR FRR and an increased number of errors False Accepts False Rejects which reduces overall system accuracy Sarhan 2009 compares the iris images by using the Hamming distance which provides a measure as to how many bits are the same between two patterns The number of degrees of freedom represented by the templates measures the complexity of iris patterns This was measured by approximating the collection of inter class Hamming distance values as binomial distribution FAR False Accept Rate is the probability that the system incorrectly matches the input pattern to the non matching template in the database
87. m 9o normaliseiris performs normalisation of the iris region by unwraping the circular region into a rectangular block of constant dimensions Usage polar_array polar noise normaliseiris image x iris y iris r_iris x pupil y pupil r pupil eyeimage filename radpixels angulardiv Arguments image the input eye image to extract iris data from x iris the x coordinate of the circle defining the iris boundary y_iris the y coordinate of the circle defining the iris boundary r_iris the radius of the circle defining the iris boundary x pupil the x coordinate of the circle defining the pupil boundary pupil the y coordinate of the circle defining the pupil boundary r_pupil the radius of the circle defining the pupil boundary eyeimage_filename original filename of the input eye image radpixels radial resolution defines vertical dimension of normalised representation angulardiv angular resolution defines horizontal dimension of normalised representation Output polar_array polar_noise function polar_array polar_noise normaliseiris image x_iris y_iris r_iris 101 x_pupil y_pupil r_pupil eyeimage_filename radpixels angulardiv global DIAGPATH radiuspixels radpixels 2 angledivisions angulardiv 1 O radiuspixels 1 theta 0 2 pi angledivisions 2 pi x_iris double x_iris y_ir
88. m Figure 4 1 Selected Iris images from Engr Panganiban s system Figure 4 2 Selected Iris images from the current system 10 20 21 24 26 28 29 30 31 32 32 37 38 vii ABSTRACT Biometrics is becoming popular nowadays due to its very useful security application These technologies use the unique characteristics of an individual in an electronic system for authentication There are numbers of biometrics technology and among those the iris recognition technology is considered the most reliable since human iris is unique and cannot be stolen The purpose of this design is to improve an existing iris recognition system developed by Engr Panganiban which is entitled CCD Camera with Near Infrared Illumination for Iris Recognition System The proposed design aims to automate the existing iris recognition system through the use of the following materials webcam Gizduino microcontroller NIR LEDs power supply and a proximity sensor The NIR LEDs which illuminates the iris were placed in a circular case attached in the webcam The iris image that would be captured in this design would only produce little noise since the light produced by the NIR LEDs would be pointing to the pupil of the eye and thus the iris image template would not be affected The automation block as its name implies automates the capturing of the webcam through the use of the sensor that is connected to the microcontroller in which
89. mmand line function varargout irisrecognition_OutputFcn hObject eventdata handles Get default command line output from handles structure varargout 1 handles output Executes on button press in exitBtn function exitBtn_Callback hObject eventdata handles close handles figure1 Executes on selection change in HdListbox function HdListbox Callback hObject eventdata handles Hints contents get hObject String returns HdListbox contents as cell array contents get hObject Value returns selected item from HdListbox Executes during object creation after setting all properties function HdListbox_CreateFcn hObject eventdata handles if ispc amp amp isequal get hObject BackgroundColor get 0 defaultUicontrolBackgroundColor set hObject BackgroundColor white end Executes on button press in EnrollBtn function EnrollBtn_Callback hObject eventdata handles frmAddName 79 999999999999999999999999999999999999999999999999999999999999 irisrecognitionprocess m function output irisrecognitionprocess eyeimage filename path for writing diagnostic images global DIAGPATH DIAGPATH diagnosticsV normalisation parameters radial res 24 angular res 240 feature encoding parameters nscales 1 minWaveLength 18 mult 1 9o not applicable if using nscales 1 sigmaOnf 0 5 eyeimage imread eyeimage filename eyeimagel imresize eyeimage
90. n be analyzed using 2D wavelets at maximum level of 5 After that a biometric template is produced Similar to Engr Panganiban s work the wavelet transform is used to extract the discriminating information in an iris pattern Only one mother wavelet is used which is the Haar because it produced the highest CRR according to Engr Panganiban s thesis The template is encoded using the patterns that yielded during the wavelet decomposition Then the algorithm will check if the template matches another template stored in the database by using its binary form to compute for the hamming distance of the two templates This is done by using the XOR operation A template can also be added to the database by using MS SQL queries t aus ma E n leg ep any d Lt T NF Figure 3 2 Schematic Diagram 129 Figure 3 2 shows the design s schematic diagram The Near Infrared LEDs serves as the lighting source The light produced by the near infrared diodes is only visible in the camera and not with the human eye It produces less noise in the image when captured than visible light The resistors used each have 5 ohms resistance This was computed using the formula R Vs Ip where Vs is the voltage source o
91. nditions for which the device is functional but do not guarantee specific performance limits Electrical Characteristics state DC and AC electrical specifications under particular test conditions which guarantee specific performance limits This assumes that the device is within the Operating Ratings Specifications are not guaranteed for parameters where no limit is given however the typical value is a good indication of device performance Note 2 The maximum junction temperature of the LM567 and LM567C is 150 C For operating at elevated temperatures devices in the TO 5 package must be derated based on a thermal resistance of 150 C W junction to ambient or 45 C W junction to case For the DIP the device must be derated based on a thermal resistance of 110 C W junction to ambient For the Small Outline package the device must be derated based on a thermal resistance of 160 C W junction to ambient Note 3 Refer to RETS567X drawing for specifications of military LM567H version www national com 2 114 SFH 484 SFH 485 Grenzwerte 7 25 C Maximum Ratings Bezeichnung Symbol Wert Einheit Parameter Symbol Value Unit Betriebs und Lagertemperatur Tus ag 40 100 C Operating and storage temperature range Sperrspannung Vp 5 V Reverse voltage Durchla amp strom Ic 100 mA Forward current Stokstrom 10 us D 0 2 5 Surge current Verlustleistung Prot 200 mW Power
92. newim newim min min newim newim newim max max newim newim newim 1 g Apply gamma function 9999999999999999999999999999999999999999999999999999999999999 addcircle m 9o ADDCIRCLE A circle generator for adding drawing weights into a Hough accumumator array 99 Usage h addcircle h c radius weight Arguments h 2D accumulator array C x y coords of centre of circle radius radius of the circle weight optional weight of values to be added to the accumulator array defaults to 1 Returns h Updated accumulator array function h addcircle h c radius weight hr hc size h if nargin weight 1 end and radius must be integers if any c fix c error Circle center must be in integer coordinates end if radius fix radius error Radius must be an integer end x O fix radius sqrt 2 costheta sqrt 1 x 2 radius 2 y round radius costheta Now fill in the 8 way symmetric points on a circle given coords px py of a point on the circle px 2 x y y X x y y c 1 y x Cull points that are outside limits validx px gt 1 amp px lt hr validy py gt 1 amp py lt hc valid find validx amp validy 100 px px valid py py valid ind px py 1 hr h ind h ind weight 9 9999999999999999999999999999999999999999999999999999999999 99 99 normaliseiris
93. ng vert horz xscaling vert yscaling horz hsize 6 sigma 1 6 sigma 1 The filter size gaussian fspecial gaussian hsize sigma im filter2 gaussian im Smoothed image im imresize im scaling rows cols size im h im 2 cols zeros rows 1 zeros rows 1 im 1 cols 1 v im 2 rows zeros 1 cols zeros 1 cols im 1 rows 1 di im 2 rows 2 cols zeros rows 1 1 zeros 1 cols zeros 1 cols zeros rows 1 1 im 1 rows 1 1 cols 1 d2 zeros 1 cols im 1 rows 1 2 cols zeros rows 1 1 zeros rows 1 1 im 2 rows 1 cols 1 zeros 1 cols h di d2 2 0 xscaling di d2 2 0 yscaling gradient sqrt X X Y Y 9o Gradient amplitude 98 or atan2 Y X Angles pi to pi or lt 0 Map angles to 0 or or neg or pi neg or or 180 pi Convert to degrees 9999999999999999999999999999999999999999999999999999999999999 adjgamma m ADJGAMMA Adjusts image gamma function g adjgamma im g Arguments im image to be processed g image gamma value Values in the range 0 1 enhance contrast of bright regions values gt 1 enhance contrast in dark regions function newim g if g lt 0 error Gamma value must be gt 0 end if isa im uint8 newim double im else newim im end rescale range 0 1
94. nnot be stolen The purpose of this design is to improve an existing iris recognition system developed by Engr Panganiban which is entitled CCD Camera with Near Infrared Illumination for Iris Recognition System The proposed design aims to automate the existing iris recognition system through the use of the following materials webcam Gizduino microcontroller NIR LEDs power supply and proximity sensor NIR LEDs which illuminates the iris were placed in a circular case attached in the webcam The iris image that would be captured in this design would only produce little noise since the light produced by the NIR LEDs would be pointing to the pupil of the eye and thus the iris image template would not be affected The automation block as its name implies automates the capturing of the webcam through the use of the sensor that is connected to the microcontroller in which is handled by the image acquisition software An additional feature of this design is the real time processing of image Once the iris was captured the software would automatically perform iris segmentation normalization template encoding and template matching It would then display if your iris is authenticated enrolled or not In matching the templates when the Hamming distance value is greater than or equal to 0 1060 the iris templates do not match but when the HD value is less than 0 1060 the iris template are from the same individual In comparing the
95. not detected by MATLAB or its DEVICEID or adapter name is invalid 2 Error at segmentiris m There are no detectable circular patterns 3 COM PORT unavailable There is no devices connected on the particular Serial COM port 4 Function or CD diagnostics or directory not found make sure that the current directory in MATLAB is the one where the m files are placed 55 Arduino Compiler 1 Error Compiling Check the syntax for errors 2 Serial Port not found The Gizduino microcontroller is connected to a different Serial Port or there is nothing connected 56 APPENDIX B Pictures of Prototype 57 APPENDIX C Program Listing 9 999999999999999999999999999999999999999999999999999999999 9 99 Arduino m classdef arduino lt handle This class defines an arduino object 9o Giampiero Campa Aug 2010 Copyright 2009 The MathWorks Inc properties SetAccess private GetAccess private aser 9 Serial Connection end methods 9o constructor connects to the board and creates an arduino object function a arduino comPort 9o Add target directories and save the updated path addpath fullfile pwd savepath check nargin if nargin 1 comPort DEMO disp Note a DEMO connection will be created disp Use a the com port e g COM5 as input argument to connect to the real board end check port if ischar comPort error The input argument must be a string e g COMS 5 end chec
96. of relevant information in an image Infrared electromagnetic radiation having a wavelength just greater than that of red light but less than that of microwaves emitted particularly by heated objects Iris the pigmented round contractile membrane of the eye suspended between the corneas and perforated by the pupil regulates the amount of light entering the eye Iris Recognition a type of pattern recognition of a person s iris recorded in a database for future attempts to determine or recognize a person s identity when the eye is viewed by a reader MATLAB Matrix Laboratory a high level programming language for technical computing from The MathWorks Natick MA used for a wide variety of scientific and engineering calculations especially for automatic control and signal processing It has an interactive environment that enables you to perform computationally intensive tasks faster than with traditional programming language such as C C and Fortran Normalization the process of efficiently organizing data in a database Proximity sensor a sensor that can detect the presence of nearby objects without any physical contact Wavelets a wave like oscillation with amplitude that starts out at zero increases and then decreases back to zero a waveform that is bounded in both frequency and duration Sensor a device such as a photoelectric cell that receives and responds to a Signal or
97. ontrol Automatic e Still Image Capture Res 2560x2048 1600x1280 2000x1600 1280x960 600x800 640x480 352x288 320x240 160x120 e Flicker Control 50 Hz 60Hz and None e Computer Port USB 2 0 port 33 CHAPTER 4 TESTING PRESENTATION AND INTERPRETATION OF DATA Automated CMOS Camera for iris recognition through proximity sensor focus on its objective of improving an existing image acquisition of the iris recognition system developed by Engr Panganiban and the design s automation In this chapter the researchers conduct experiments to identify whether the hardware and software design meet the criteria for an effective iris recognition system Several observations and assessments are provided together with reliable measurements or data that will support the researcher s remarks SENSOR OUTPUT TEST The proximity sensor automates the system by detecting whether the person is at the correct distance and position before capturing the subject s iris Further testing on the proximity sensor was done because there has been a suspected glitch found on the proximity sensor Table 4 1 Proximity Sensor Settings SETTINGS Position Placed on top of the camera Input Person s forehead 34 Table 4 2 Sensor Output Testing DISTANCE cm Red LED Status Output 1 Solid Red Light 2 Solid Red Light 3 Solid Red Light 4 Solid Red Light 5 Flickering Red Light 6 No light 7
98. ontroller manufactured and produced by E Gizmo The image acquisition software is developed using MATLAB R2009a The next part is the Iris Capture block It consists of the webcam and the NIR LEDs The webcam is connected to the computer through its USB cord The NIR LEDs are the one responsible for the visibility of the iris to the webcam If the image acquisition software tells the webcam to capture the webcam will do so and an iris image will be produced The final part is the iris recognition algorithm The iris recognition algorithm starts with the iris segmentation process It is based on the circular Hough transform which is similar to the equation of a circle Z Y c Since the iris of the eye is ideally shaped like a circle the Hough transform is used to determine the properties of geometric objects found in an image like circles and lines Canny edge detection is used to detect edges of shapes It is developed by John F Canny in 1986 Horizontal lines are drawn on the top and bottom eyelid to separate the iris and two circles are drawn one for the pupil and the other one for the iris The value of the iris radius to be used ranges from 75 to 85 pixels and for the pupil radius ranges from 20 to 60 pixels After the iris is segmented it is normalized In normalization the segmented iris is converted to a rectangular shaped strip with fixed dimensions This process uses Daugman s rubber sheet model The image will the
99. openness errstr arduino checkser a aser open if isempty errstr error errstr end send mode pin and value fwrite a aser 48 97 pin 48 val uchar end detach servo 1 or 2 if pins 10 or 9 are used if pin 10 pin 9 a servoDetach 11 pin end 64 store 0 for input and 1 for output a pins pin val elseif nargin 2 print pin mode for the requested pin mode UNASSIGNED set as INPUT set as OUTPUT disp Digital Pin num2str pin is currently mode 2 a pins pin else print pin mode for each pin mode UNASSIGNED set as INPUT set as OUTPUT for i 2 19 disp Digital Pin num2str i 02d is currently mode 2 a pins i end end end pinmode digital read function val digitalRead a pin val a digitalRead pin performs digital input on a given arduino pin The first argument before the function name a is the arduino object The argument pin is the number of the digital pin 2 to 19 where the digital input needs to be performed Note that the digital pins from 0 to 13 are located on the upper right part of the board while the digital pins from 14 to 19 are better known as analog input pins and are located in the lower right corner of the board Example val a digitalRead 4 reads pin 4 00 00 00 0 0 00 0 0 00 0 0 00 0 00 00 0000000000 0000000000 00000000 ARGUMENT CHECKING 65 check n
100. ose Executes on button press in btnCancel function btnCancel_Callback hObject eventdata handles close 9 9999999999 99 9 9 9999999 99 99 999999999 999999999 9 9 9999999 9 9 9 999999 99 99 9 segmentiris m segmentiris peforms automatic segmentation of the iris region from an eye image Also isolates noise areas such as occluding eyelids and eyelashes Usage circleiris circlepupil imagewithnoise segmentiris image Arguments eyeimage the input eye image Output 9o circleiris centre coordinates and radius of the detected iris boundary circlepupil centre coordinates and radius of the detected pupil boundary imagewithnoise original eye image but with location of noise marked with NaN values function circleiris circlepupil imagewithnoise segmentiris eyeimage Ipupilradius 20 upupilradius 75 lirisradius 80 uirisradius 95 define scaling factor to speed up Hough transform scaling 0 4 reflecthres 240 find the iris boundary 84 row col findcircle eyeimage lirisradius uirisradius scaling 2 0 20 0 19 1 00 0 00 circleiris row col r rowd double row cold double col rd double r irl round rowd rd iru round rowd rd icl round cold rd icu round cold rd imgsize size eyeimage if irl lt 1 1 if icl lt 1 icl 1 end if iru gt imgsize 1
101. pF tr Rxd 1 40 ns Signal 0 Signal Rxd Pulse Width of Input pulse length 20 us 9 6 kbit tpw 12 10 20 us SIR Mode Input pulse length 1 41 us 1 2 bit us 115 2 kbit s length Rxd Pulse Width of 110 260 ns Output Signal 50 1 152 Mbit s MIR Mode Input Irradiance 100 mW m2 10 25 ns Edge MIR Mode 1 152 Mbit s Latency 120 us Transmitter IRED Operating Current R1 7 2 Q Vec 5 0 V 0 55 A Output Radiant Intensity Vcc 5 0 V 0 15 1 350 mW sr see Figure 3 Txd High SD Low R1 7 2Q Output Radiant Intensity Vcc 5 0 V a 0 15 0 04 mW sr Txd Low SD High Receiver is inactive as long as SD High R1 7 2Q Output Radiant Intensity Angle of Half Intensity Peak Emission 900 nm Wavelength Duration 1 152 Mbit s Optical Output Pulse Input pulse width t lt 80 us us Duration Input pulse width t gt 80 us 80 us Optical Rise Time 40 ns Fall Time Optical Overshoot 10 R1 control series resistor for current limitation Document Number 82535 www vishay com Rev A1 0 13 Oct 00 5 11 121 BCEE FAIRCHILD Eeer SEMICONDUCTOR MC78XX LM 78XX IMC 78XXA 3 Terminal 1A Positive Voltage Regulator www fairchildsemi com Features Description Output Current up to 1 The MC78XX LM78XX MC78XXA series of three Output Voltages of 5 6 8 9 10 12 15 18 24V terminal positive regulators are available in the
102. pixels which can be calculated by multiplying pixel columns by pixel rows and dividing by one million According to the same standards the number of effective pixels that an image sensor or digital camera has is the count of elementary pixel sensors that contribute to the final image as opposed to the number oftotal pixels which includes unused or light shielded pixels around the edges Image noise is the random variation of brightness or color information in images produced by the sensor and circuitry of a scanner or digital camera Image noise can also originate in film grain and in the unavoidable shot noise of an ideal photon detector It is generally regarded as an undesirable by product of image capture According to Makoto Shohara noise is dependent on the background color and luminance They conducted subjective and quantitative experiments for three noise models using a modified grayscale method The subjective experiment results showed the perceived color noise depends on the background color but the perceived luminance noise does not Proximity Sensor A proximity sensor detects the presence of nearby objects without any physical contact This type of sensor emits a beam of electromagnetic radiation such as infrared and looks for changes in the field or a return signal The proximity sensor automates the camera by deciding on whether the target is positioned for capture Iris Image Acquisition Image acquisition depends hi
103. polar_array2 coords 0 5 avg sum sum polar_array2 size polar_array 1 size polar_array 2 polar_array coords avg 9 9999999999 99 9999999999 99 99999999999999999 99 9999999 9 9 9 9 999999 99 9 99 shiftbits m function newtemplate shiftbits template noshifts newtemplate zeros size template tempsize size template 2 s 0 p round tempsize s if noshifts newtemplate template if noshifts is negative then shift towards the left elseif noshifts lt 0 x 1 p newtemplate x template s x x p 1 tempsize newtemplate x template x p else x s 1 tempsize newtemplate x template x s 1 5 105 newtemplate x template p x end 999999999999999999999999999999999999999999999999999999999999 gethammingdistance m function HD gethammingdistance template1 template2 rowcount size template1 2 templatea zeros size template1 for int 1 rowcount if template1 1 int 1 template1 1 int 0 templatea 1 int str2num template1 1 int end end rowcount size template2 2 templateb zeros size template2 for int 1 rowcount if template2 1 int 1 template2 1 int 0 templateb 1 int str2num template2 1 int end end templatea logical templatea templateb logical templateb HD NaN for shifts 8 8 templateis shiftbits templatea shifts totalbits size template1s 1 size t
104. pple voltage formed in the rectification process The regulator makes the voltage stable and accurate A heat sink was attached to dissipate the heat produced by the circuit 23 POWER SUPPLY with SV output 24 ls Stm Din Die 30m Yin Ga tie Y un Yin Yo s foe fo fe gt iagram EERE REERRA UREA zenano ic D Schemat Figure 3 3 The Near Infrared LEDs serves as the lighting source The light produced by the near infrared diodes is only visible in the camera and not with the human eye It produces less noise in the image when captured than visible light The resistors used each have 5 ohms resistance This was computed using the formula Vs VF Ir where Vs is the voltage source of 5 V Vr is the voltage drop of 1 5 V and an Ir is a current of 100 mA The formula would produce a resistance of 35 ohms But considering that we are to connect in parallel four rows of 3 NIR LEDs in series the resulting resistance value R connected in series with the 3 NIR LEDs on each row would be 5 ohms The proximity sensor detects the presence of nearby objects without any physical contact This type of sensor emits a beam of electromagnetic radiation such as infrared and looks for changes in the field or a return signal This gives the appropriate signal to the image capturing software when the s
105. prove the existing Image Acquisition of the Iris Recognition System by Engr Panganiban Specifically for the success of this design the following objectives must be met 6 The Camera to be used with the help of the NIR LEDs must be able to produce an image of the subject s iris 7 NIR LEDs must be located where it would give enough IR light to the subject s iris This would help make the iris more visible to the camera and to the image for capture 8 The Proximity sensor should be installed to the system which would detect whether the person is at the correct distance and position before capturing the subject s iris 9 The system must be able to recognize the difference between the irises to be processed through Hamming distance values and show the separation of classes through degree of freedom DoF 10 The system must have a DoF improvement on Engr Panganiban s design C Impact of the Design The design is an Automated Iris Recognition System it is generally made for improving its image acquisition This would capture an image of the iris Nowadays this biometric technology shows an increasing promise on the security system for it studies the unchanging measurable biological characteristics that are unique to each individual Among the existing biometric devices and scanners available today it is generally conceded that iris recognition is the most accurate The design can be used as a prototype which can be implemented
106. puter Engineering Ik 9 ul Felicito S Caluyo Dean School of EECE ii ACKNOWLEDGEMENT It is with great pleasure that we acknowledge the efforts of those individuals who have taken part to the development of this study We would like to thank our adviser Engr Ayra Panganiban for guiding us and sharing her time and knowledge on the study To the panel members who have allotted their time for our oral presentation and for checking our paper for the necessary revisions To our professor Engr Noel Linsangan who tolerantly helped us with the necessary revisions needed for our paper provided us handy guidelines and documents for the completion of this project and inspired us to strive for the betterment of our research To our friends and colleagues who helped and supported us with this design To our parents for their unending support and encouragement and Above all we humbly give our sincerest gratitude to the Almighty God for giving us the strength patience unfading guidance and for imparting us the wisdom to accomplish this paper iii TABLE OF CONTENTS TITLE PAGE APPROVAL SHEET ACKNOWLEDGEMENT TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES ABSTRACT Chapter 1 DESIGN BACKGROUND AND INTRODUCTION BACKGROUND STATEMENT OF THE PROBLEM OBJECTIVES OF THE DESIGN IMPACT OF THE DESIGN DESIGN CONSTRAINTS DEFINITION OF TERMS Chapter 2 REVIEW OF RELATED DESIGN LITERATURES AND STUDIES IRIS RECOGNITION TECHN
107. r of pixel rows height for example as 640 by 480 Another popular convention is to cite resolution as the total number of pixels in the image typically given as number of megapixels which can be calculated by multiplying pixel columns by pixel rows and dividing by one million According to the same standards the number of effective pixels that an image sensor or digital camera has is the count of elementary pixel sensors that contribute to the final image as opposed to the number oftotal pixels which includes unused or light shielded pixels around the edges Image noise is the random variation of brightness or color information in images produced by the sensor and circuitry of a scanner or digital camera Image noise can also originate in film grain and in the unavoidable shot noise of an ideal photon detector It is generally regarded as an undesirable by product of image capture According to Makoto Shohara noise is dependent on the background color and luminance They conducted subjective and quantitative experiments for three noise models using a modified grayscale method The subjective experiment results showed the perceived color noise depends on the background color but the perceived luminance noise does not 13 Proximity Sensor A proximity sensor detects the presence of nearby objects without any physical contact This type of sensor emits a beam of electromagnetic radiation such as infrared and looks for changes in the fiel
108. radius cos angle x and y offset of points at specified radius and angle yoff radius sin angle from each reference position hfrac xoff floor xoff 9o Fractional offset of xoff relative to integer location vfrac yoff floor yoff Fractional offset of yoff relative to integer location orient fix orient 1 Orientations start at 0 degrees but arrays start with index 1 Now run through the image interpolating grey values on each side of the centre pixel to be used for the non maximal suppression for row iradius 1 rows iradius for col iradius 1 cols iradius or orient row col Index into precomputed arrays x col xoff or y location on one side of the point in question y row yoff or fx floor x Get integer pixel locations that surround location x y cx ceil x fy floor y cy ceil y tl inimage fy fx Value at top left integer pixel location tr inimage fy cx top right bl inimage cy fx bottom left br inimage cy cx bottom right upperavg tl hfrac or tr tl Now use bilinear interpolation to loweravg bl hfrac or br bl estimate value at x y 88 v1 upperavg vfrac or loweravg upperavg if inimage row col gt vi We need to check the value on the other side x col xoff or x y location on the other side of the point in question y row yoff or fx floor x cx ceil x
109. rejects an authorized user or a correct template which is computed using the formula FRR Pinta n where Pintra is the number of HD values that fall under Poor Quality of the intra class distribution and n is the total number of samples The Equal Error Rate EER compares the accuracy of devices The lower the EER the more accurate the system is considered to be The characteristic of the wavelet transform are the concept used in encoding iris bit patterns These metrics are useful in achieving the accuracy and efficiency of wavelet coefficients 18 Chapter 3 DESIGN PROCEDURES The design is an automated iris recognition system with a hardware that consists of a webcam Gizduino microcontroller NIR LEDs power supply and a proximity sensor Figure 3 1 illustrates the conceptual framework of the design The proximity sensor sense objects that are in front of its transceiver in the design the face of the person is the target of the proximity sensor When the target is within the detecting range of the sensor the sensor will output a signal that is treated as an input to the microcontroller and this will command the webcam to capture an image Through proper alignment this captured image would be the eye of the subject The NIR light serves as the illuminations to acquire iris of the eye visible to the webcam After the webcam captures the eye the image acquisition software produces the iris image that will be sent to the iris recognit
110. river file named ArduinoUNO inf located in the Drivers folder of the Arduino Software download not the FTDI USB Drivers sub directory 2 3 8 Windows will complete the driver installation from there User s Manual How to use the Gizduino microcontroller and software 1 Connect the Gizduino microcontroller to the USB port of the computer 2 Open the Arduino Compiler 3 From the Menu Bar select Tools then choose Serial Port and select the designated port where the microcontroller is connected 51 4 On the Arduino workspace enter the arduino input output server code that is listed on Appendix C 5 Compile the code by pressing Verify button to check for errors before uploading it to the microcontroller 6 To upload the code to the microcontroller press the Upload button 7 Wait until the uploading is finished A message Uploading Successful will be displayed How to use the MATLAB iris recognition software 1 Open a MATLAB workspace 2 In the directory icon browse the folder where the source code is located in this case the programs are stored under a folder named Design Project 3 In the command directory area make sure that all files and folders are properly referenced Note highlight all folders under the Design Project folder then right click Choose add to path gt all folders and sub folders 4 In the current directory right click on the irisrecognition m
111. round lradius scaling uradsc round uradius scaling rd round uradius scaling Iradius scaling generate the edge image 12 or canny image sigma scaling vert horz 1 9 to 1 5 for gamma adjgamma L2 1 8 I4 nonmaxsup I3 1 5 edgeimage hysthresh I4 hithres lowthres perform the circular Hough transform h houghcircle edgeimage lradsc uradsc maxtotal 0 find the maximum in the Hough space and hence 9o the parameters of the circle for i 1 rd layer 1 maxlayer max max layer if maxlayer maxtotal maxtotal maxlayer r int32 Iradsc i scaling row col find layer maxlayer row int32 row 1 scaling 9o returns only first max value col int32 col 1 scaling end end 97 9 9999999999 99 9 99999999 999 9 99999999999999999 99 9999999 9 9 99 9999999 9 99 CANNY Canny edge detection Function to perform Canny edge detection Usage gradient or canny im sigma Arguments im image to be procesed sigma standard deviation of Gaussian smoothing filter typically 1 scaling factor to reduce input image by vert weighting for vertical gradients horz weighting for horizontal gradients 9o Returns gradient edge strength image gradient amplitude or orientation image in degrees 0 180 positive anti clockwise function gradient or canny im sigma scali
112. s Proper choice of threshold value is needed in the success of the iris recognition But if there were instances where a clear decision cannot be made based on a preset threshold value the comparison between the relative values of Hamming distances can lead to correct recognition The determination of identity in her study was based on both the threshold value and on a comparison of HD values The test metrics proved that her proposed algorithm has a high recognition rate Biometric Test Metrics Ives et al 2005 determined the consequences of compression through the analysing the compression rate Also each pair of curves False Rejection Rate FRR and False Accept Rate FAR represents the comparison of each compressed database against the original database An original versus original comparison is included as a baseline The compression ratio increases the FAR curve remains virtually unchanged while the FRR curves move further to the right which causes an increased Equal Error Rate EER where FAR FRR and an increased number of errors False Accepts False Rejects which reduces overall system accuracy 16 Sarhan 2009 compares the iris images by using the Hamming distance which provides a measure as to how many bits are the same between two patterns The number of degrees of freedom represented by the templates measures the complexity of iris patterns This was measured by approximating the collection of inter class Hamming
113. s the status of digital pin 10 a pinMode 5 prints the status of digital pin 5 a pinMode prints the status of all pins 9 00 00 909 00900 909 909 909 909 909 900 9 ARGUMENT CHECKING On n 00 00 D n 000 0 00 00 0 0 00 00 Din 00 0 0 00 00 00 00 0000 9 o9 o9 o9 o9 o check nargin if nargin gt 3 error This function cannot have more than 3 arguments object pin and 5 end first argument must be the arduino variable if isa a arduino error The first argument must be arduino variable end if pin argument is there check it if nargin2 1 63 errstr arduino checknum pin pin number 2 19 if isempty errstr error errstr end end if str argument is there check it if nargin gt 2 errstr arduino checkstr str pin mode input output if isempty errstr error errstr end end perform the requested action if nargin 3 check a aser for validity errstr arduino checkser a aser valid if isempty errstr error errstr end 9 59 59 59 5 Din o o 00 0 0000 000 D n Din Die Din Dien Din D n Din Di O Din CHANGE PIN MODE 000 0000 00 0 0 0 00 0 0 00 0 0 000 0 00 0 0 0000 00 00 00 00 00 00 0 Die 0 00 900 9000 assign value if lower str 1 o val 1 else val 0 end if strcmpi get a aser Port DEMO handle demo mode here average digital output delay pause 0 0087 else do the actual action here check a aser for
114. send mode pin and value fwrite a aser 52 97 pin val uchar 71 end end analogwrite end methods methods Static static methods function errstr checknum num description allowed errstr arduino checknum num description allowed Checks numeric argument This function checks the first argument num described in the string given as a second argument to make sure that it is real scalar and that it is equal to one of the entries of the vector of allowed values given as a third argument If the check is successful then the returned argument is empty otherwise it is a string specifying the type of error preliminary check nargin if narginv 3 error checknum needs 3 arguments please read the help end preliminary check description if isempty description ischar description error checknum second argument must be a string end preliminary check allowed if isempty allowed isnumeric allowed error checknum third argument must be a numeric vector end initialize error string errstr check num for type if isnumeric num errstr The description must be return 72 end check num for size if numel num 1 errstr The description must be a scalar return end 9o check num for realness if isreal num errstr The description must be a real value return end check num against allowed values if any al
115. ses it extracts the iris feature and encodes the template into bits After that the system compares the encoded template with all the templates stored in the database When a match is found the program displays a message box telling that the person s iris is authenticated and is registered on the database and then the system prepares for the next capture by going back to the distance inspection But when it s not found the program displays a message box again however telling that it is not found and it s not authenticated Also the system asks if the unauthenticated iris template is to be enrolled in the database or not If it would be enrolled then the iris template and its path are inserted into the database and then the system goes back to the distance inspection Else if it s not to be enrolled then the system just goes back to the distance inspection 27 IrisDataBankDesign Column Name Data Type Key Type Allow Null IrisId Int PK No IrisPath varchar 50 NONE Yes IrisTemplate varchar MAX NONE Yes Figure 3 5 Relational Model The template bits are stored in a database using Microsoft SQL 2005 Express edition In Fig 3 5 the IrisId field is set to auto increment by 1 and the primary key While the IrisPath and IrisTemplate depends on the output of the system which is inserted to the database Prototype Development The design prototype has both hardware and software components The hardware
116. sheet which was unwrapped into a rectangular block with constant polar dimensions to eliminate dimensional inconsistencies between iris regions Then the features of the iris were encoded by convolving the normalised iris region with 1D Log Gabor filters and phase quantising the output in order to produce a bit wise biometric template The Hamming distance was chosen as a matching metric This gave a measure on the number of bits that disagreed between two templates A failure of statistical independence between two templates would result in a match This means that the two templates were considered to have been generated from the same iris if the Hamming distance produced was lower than a set Hamming distance In the proposed algorithm of Panganiban 2010 the feature vector was encoded using Haar and Biorthogonal wavelet families at various levels of decomposition Vertical coefficients were used for implementation because of the dominant features of the normalized images that were oriented vertically Hamming distance was used to define the inter class and intra class relationships of the templates The computed number of degrees of freedom which was based on the mean and the standard deviation of the binomial distribution demonstrated the separation of iris classes Proper choice of threshold value is needed in the success of the iris recognition But if there were instances where a clear decision cannot be made based on a preset threshold va
117. sor would indicate that the human eye is within the range of 4 to 5 cm Every time an object is sensed the red LED generates a solid light and the camera captures an image of the object The system does not involve iris image processing and matching of individuals with eye disorders or contact lenses Since with these situations the iris image will be affected Also the system will only work properly when the captured image is an iris otherwise it will result to an error The speed of the system is limited by the computer specifications where the software is deployed The recommended system requirements for the software application is a multi core 2 20 GHz or higher for the CPU a 4 00 GB or higher for the RAM and Windows 7 for the operating system DEFINITION OF TERMS Authentication the process of determining whether someone or something is enrolled in the system or has authorized to be Biometrics the science and technology of measuring and analyzing biological data refers to technologies that measure and analyze human characteristics such as fingerprints eye retinas and irises voice patterns facial patterns and hand measurements for authentication purposes Camera a device that converts images into electrical signals for television CMOS Complementary Metal Oxide Semiconductor a semiconductor technology used in the transistors that are manufactured into most of microchips Database the collection of data
118. stimulus Segment the part into which something is divided Segmentation the process of partitioning a digital image into multiple segment in this case the process of locating the iris region Software a collection of computer programs and related data that provide the instructions telling a computer what to do and how to do it CHAPTER 2 REVIEW OF RELATED DESIGN LITERATURES AND STUDIES Iris Recognition Technology Biometrics became popular in security applications due to its personal identification and verification based on the physiological and behavioural characteristics of the subject Among the existing biometric technologies it is iris recognition that is considered promising which uses the apparent pattern of the human iris Panganiban 2010 The iris is a muscle within the eye that regulates the size of the pupil which controls the amount of light that enters the eye It is the colored portion of the eye with coloring based on the amount of melatonin pigment within the muscle The coloration and structure of the iris is genetically linked but the details of the patterns are not National Science and Technology Council 2006 Retina Figure 2 1 Iris Diagram 10 Irises contain approximately 266 distinctive characteristics about 173 of which are used to create the iris template and serves as a basis for biometric identification of individuals Iris patterns possess high inter class dependency and lo
119. the light reflection will be located in the pupil it would not affect the iris segmentation and that the iris template The case of the camera also lessens the noise since it blocks other factors that might affect the iris image and results The proximity sensor has a delay of 5 seconds before it sends signal for the webcam to capture the iris image There is a delay so that the user can position his or her eye properly to the device 44 Also the results showed that when the Hamming distance value is greater than or equal to 0 1060 the iris templates do not match The Intra class comparison of Haar Wavelet at level 4 vertical coefficient shows that when the HD value is less than 0 1060 the iris templates are from the same individual From the results of the Hamming Distance in inter class comparison the Degrees of Freedom DoF computed is 80 which is higher than of Engr Panganiban s work which is equal to 50 This shows that the comparison of iris templates in our design is more accurate 45 RECOMMENDATION Although the obtained results proved that the design is sufficient for iris recognition the following are still recommended for the improvement of the system s performance 1 The proximity sensor may be replaced by an algorithm such as pattern recognition that will allow the software to capture the iris image once a circular shape is near the camera 2 The digital camera can be converted to an Infrared Camera which woul
120. tion and the interoperability are highly dependent in the quality of the iris image There are different factors that affect the image quality namely defocus blur motion blur off angle occlusion lighting specular reflection and pixel counts The camera must possess excellent imaging performance in order to produce accurate results In a CMOS Complementary Metal Oxide Semiconductor Image sensor each pixel has its own charge to voltage conversion CMOS image sensor often includes amplifiers noise correction and digitalization circuits so that the chip outputs digital bits Because of these features the design complexity increases and the area available for light capture decreases Iris Image Quality Metrics Iris Image Quality Document in Part 6 of ISO IEC 29794 establishes terms and definitions that are useful in the specification characterization and test of iris image quality Some of the common quality metrics for iris images are the following Sharpness Contrast Gray scale density Iris boundary shape Motion blur Noise and Usable Iris Area Sharpness is the factor which determines the amount of detail an image can convey It is affected by the lens particularly the design and manufacturing quality focal length aperture and distance from the image center as well as the sensor pixel count and anti aliasing filter In the field sharpness is affected by camera shake focus accuracy and atmospheric disturbances like th
121. ubject is in the right position for iris image acquisition The Gizduino microcontroller is a clone of Arduino microcontroller made by the company E Gizmo It has a built in ATMEGA microcontroller and PL2303 USB to RS 232 Bridge Controller 25 Software Development Initialize camera and microcontroller settings gizduinoPort 0 gizduinoPort digitalRead 8 0 capture image y iris image processing Y match template with the irises stored in the database display Authenticated No display Not Authenticated No enroll the iris to the database insert iris template and path to database End Figure 3 4 System Flowchart 26 Figure 3 4 illustrates the flowchart of the system First the system initializes the camera and the microcontroller settings Then it checks whether the Gizduino microcontroller is connected or not by checking the value of gizduinoPort While it is equal to zero the system will end its process But while its value is not equal to zero meaning the MCU is still connected it inspects if the person s face is within the correct distance by checking the value of gizduinoPort digitalRead 8 If the value is zero it means that the distance is correct according to the proximity sensor and the program triggers the camera to capture the iris image After capturing the image the system proces
122. utput Voltage 5 0mA lt lo 1 0A Po 15W 7V to 20V 25 Vo 7 7V to 25V 4 0 Line Regulation Note1 Regline Ty 25 oc DEER Vi 8V to 12V 16 Load Regulation Note1 Regload Ty 25 C lo 250mA to mV 50 750mA o nese 89 A lo 5mA to 1 0A 0 03 0 5 f 120Hz LI E e lelie Dropout Voltage lo 1A TJ 25 C Output Resistance Output Resistance ro f 1KHz Short Circuit Current 35V TA 25 C Peak Current 25 C Note 1 Load and line regulation are specified at constant junction temperature Changes in Vo due to heating effects must be taken into account separately Pulse testing with low duty is used 123 APPENDIX E IEEE Article Format 124 AUTOMATED IRIS RECOGNITION SYSTEM USING CMOS CAMERA WITH PROXIMITY SENSOR Paulo R Flores Hazel Ann T Poligratis Angelo S Victa School of Electrical Electronics and Computer Engineering Mapua Institute of Technology Muralla St Intramuros Manila Philippines Abstract Biometrics is becoming popular nowadays due to its very useful security application These technologies use the unique characteristics of an individual in an electronic system for authentication There are numbers of biometrics technology and among those the iris recognition technology is considered the most reliable since human iris is unique and ca
123. w intra class dependency Daugman 1993 Image Quality According to Kalka et al the performance of the iris recognition system particularly recognition and segmentation and the interoperability are highly dependent in the quality of the iris image There are different factors that affect the image quality namely defocus blur motion blur off angle occlusion lighting specular reflection and pixel counts The camera must possess excellent imaging performance in order to produce accurate results In a CMOS Complementary Metal Oxide Semiconductor Image sensor each pixel has its own charge to voltage conversion CMOS image sensor often includes amplifiers noise correction and digitalization circuits so that the chip outputs digital bits Because of these features the design complexity increases and the area available for light capture decreases Iris Image Quality Metrics Iris Image Quality Document in Part 6 of ISO IEC 29794 establishes terms and definitions that are useful in the specification characterization and test of iris image quality Some of the common quality metrics for iris images are the 11 following Sharpness Contrast Gray scale density Iris boundary shape Motion blur Noise and Usable Iris Area Sharpness is the factor which determines the amount of detail an image can convey It is affected by the lens particularly the design and manufacturing quality focal length aperture and distance from the ima
124. w surface mounting Functional Block Diagram SD Mode Voc AGC Logic Txd Pin Description IRED Cathode Open Drain Driver GND Figure 1 Functional Block Diagram Pin Number Function Description Active 1 IRED Anode IRED anode to be externally connected to Vcc through a current control resistor This pin is allowed to be supplied from an uncontrolled power supply separated from the con trolled Vcc supply 2 IRED Cathode IRED cathode internally connected to driver transistor 3 Txd Transmit Data Input HIGH 4 Rxd Pin is floating when device is in shutdown mode LOW 5 SD Mode Shutdown Mode HIGH 6 Voc Supply Voltage 7 Mode HIGH High speed mode LOW Low speed mode SIR only see chapter Mode Switching 8 GND Ground Baby Face Universal Detector 3 15 16107 Figure 2 Pinnings IRED www vishay com 2 11 Document Number 82535 Rev A1 0 13 Oct 00 118 Wu TFDU5102 v Vishay Telefunken Absolute Maximum Ratings Reference point Pin GND unless otherwise noted Typical values are for DESIGN AID ONLY not guaranteed nor subject to production testing Parameters TestCondiions Symbol Min Typ Max Unit Supply Voltage Range 0 V Vcc lt 6 V V Transceiver Supply Voltage Range 0 V Vcc4 6V Transmitter Input Currents For all Pins Ex
125. wchart Figure 3 3 illustrates the flowchart of the system First the system initializes the camera and the microcontroller settings Then it checks whether the Gizduino microcontroller is connected or not by checking the value of gizduinoPort While it is equal to zero the system will end its process But while its value is not equal to zero meaning the MCU is still connected it inspects if the person s face is within the correct distance by checking the value of gizduinoPort digitalRead 8 If the value is zero it means that the distance is correct according to the proximity sensor and the program triggers the camera to capture the iris image After capturing the image the system processes it extracts the iris feature and encodes the template into bits After that the system compares the encoded template with all the templates stored in the database When a match is found the program displays a message box telling that the person s iris is authenticated and is registered on the database and then the system prepares for the next capture by going back to the distance inspection But when it s not found the program displays a message box again however telling that it is not found and it s not authenticated Also the system asks if the unauthenticated iris template is to be enrolled in the database or not If it would be enrolled then the iris template and its path are inserted into the database and then the system goes back to the
126. y nscales minWaveLength mult sigmaOnf output encode polar_array 999 9999999999 99 99999999 99 9999999999 99 9 9999999999 9 999999 9 99999 9 99 myWait m Waits for the specified number of seconds function myWait DeltaT if DeltaT gt 0 end condition t timer timerfcn myWait 0 StartDelay DeltaT start t wait t end 81 9 99 9999999999999999999999999999999999999999999999999999999 99 99 999 frmAddName m function varargout frmAddName varargin Begin initialization code DO NOT EDIT gui_Singleton 1 gui State struct gui Name mfilename gui Singleton gui Singleton Out OpeningFcn frmAddName_OpeningFcn gui OutputFcn frmAddName_OutputF cn out LayoutFcn gui Callback if nargin amp amp ischar varargin 1 gui State gui Callback str2func varargin 1 end if nargout varargout 1 nargout gui mainfcn gui State varargin else gui mainfcn gui State varargin end End initialization code DO NOT EDIT 9o Executes just before frmAddName is made visible function frmAddName OpeningFcn hObject eventdata handles varargin Choose default command line output for frmAddName handles output hObject 9 o Update handles structure guidata hObject handles pixels set handles frmAddName Units pixels get your display size screenSize get 0 5 calculate the center of

automated iris recognition system using cmos camera with proximity

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