sondosaabed / Iris-of-eyes-recognition

A Biometric Authentication system using Iris. Enrollment and Authentication Modules. End to End, Iris Segmentation Free using DCNNs, Accuracy of 93.15%

Home Page:https://www.datacamp.com/completed/statement-of-accomplishment/course/249420257b1e54b4417e85791ccfb45818688202

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Iris-of-eyes-recognition

In this project, a Biometric Authentication system using the Iris biometric authentication method is designed. The approach taken is using the CASIA-Thousand-IRIS dataset and model it using the Deep Convultional Neural Network Architicture, with the minimum image-preprocessing such as resizing with keeping the aspect ratiio and normalization. It is an end-to-end technique without performing segmentaion of the IRIS itself. The results are promising, even without perfroing training on augmentation, the testing accuracy has reached (91.10%). Finally, for the proof of the (biometric authentication system concept) a simple mobile application is designed and the model is deployed on it (IrisRecognizer) as it was exported to it's liter version were default quantization is performed.

Model Training (Accuracy and Loss Learning Curves)

329887758-08852261-6504-40b3-b25a-c7c33f251219

Example of results on testing dataset

image

GUI Authenticater Module

In a biometric authentication system there has to be an authenticter part for it. A simple mobile application is done for the concept:

Refer to this repository: https://github.com/sondosaabed/IrisRecognizer

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A Biometric Authentication system using Iris. Enrollment and Authentication Modules. End to End, Iris Segmentation Free using DCNNs, Accuracy of 93.15%

https://www.datacamp.com/completed/statement-of-accomplishment/course/249420257b1e54b4417e85791ccfb45818688202

License:MIT License


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