6.iris recognition using machine learning technique

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This document describes an iris recognition project that uses a CNN model trained on the CASIA iris image dataset to recognize people. The CNN model is trained by extracting iris features from the CASIA images using Hough circle detection and achieves 100% accuracy on the training data. Graphs show the loss decreasing and accuracy increasing over epochs during training. The trained model can then be used to recognize people in new iris images by predicting the person ID. It correctly identifies test images from both outside the dataset and from within the CASIA images.

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IrisRecognitionusingMachine LearningTechnique
In thisprojectto recognize personfromIRISwe are usingCASIA IRISdatasetwhichcontainsimages
from108 peoplesandbyusingthisdatasetwe are trainingCNN model andthenwe can use thisCNN
model topredict/recognize persons.TotrainCNN model we are extractingIRISfeaturesbyusing
HoughCircles algorithmwhichextractIRIScircle fromeye images.Below screenshotsshowing
datasetwithpersonidand thisdatasetsavedinside ‘CASIA1’folder
In above screenwe have IRISimagesfrom108 peoplesandjustgoinside anyfoldertogetthat
personIRISimageslike belowscreen

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SCREEN SHOTS
To run projectdouble clickon‘run.bat’file togetbelow screen
In above screenclickon‘UploadIrisDataset’buttonand uploaddatasetfolder
In above screenselectinganduploading‘CASIA1’folderandthenclickon‘SelectFolder’buttonto
loaddatasetand to getbelowscreen

Venkat Java Projects
Mobile:+91 9966499110
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In above screendatasetloadedandnowclickon‘Generate &Load CNN Model’buttonto generate
CNN model fromloadeddataset
In above screen683 imagesloadedfromdifferent108 peoplesandwe gotit predictionaccuracyas
100%. Nowmodel isreadyandnow clickon‘Accuracy & Loss Graph’ buttonto getbelow graph

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Mobile:+91 9966499110
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In above graphred line representsCNN modellossvalue andwe can see at firstiterationlosswas
more than 4% and whenepochincreasesthenLOSSvalue reduce to0 andgreenline represents
accuracy and at firstiterationaccuracy was0% and whenepoch/iterationsof modelincreasesthen
accuracy reachedto 100% and inabove graph x-axisrepresentsEPOCHandy-axisrepresents
accuracy and lossvalues.Nowclickon‘UploadIrisTestImage & Recognize’buttonanduploadany
testimage and thenCNN will recognizepersonIDfromthatIRIS image.If youwantyou can upload
testimage fromCASIA folderalsoandyouwill see predictionwill be 100% correct
In above screenselectinganduploading‘b.jpg’file andthen clickon‘Open’buttontogetbelow
screen

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Mobile:+91 9966499110
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In above screenfromuploadedimage we extractIRISfeatureswhich isdisplayinginfirstimage and
thenthisimage feedstoCNN andthenCNN predictedthatIRISbelongtopersonID 15. Now I will
uploadone image fromCASIA folderandthentestwhetherCNN will predictcorrectlyornot
In above screenfromCASIA folderIamuploadingIRISof personID38 andthenclick‘Open’button
to getbelowresult

Venkat Java Projects
Mobile:+91 9966499110
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In above screenCNN predictedIDis38 whichis100% correct

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6.iris recognition using machine learning technique

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