A Computer Vision System for Iris Recognition Based on Deep Learning

Abstract

Biometric systems are playing an important role in identifying a person, thus contributing to global security. There are many possible biometrics, for example height, DNA, handwriting etc., but computer vision based biometrics have found an important place in the domain of human identification. Computer vision based biometrics include identification of face, fingerprints, iris etc. and using their abilities to create efficient authentication systems. In this paper, we work on a dataset [1] of iris images and make use of deep learning to identify and verify the iris of a person. Hyperparameter tuning for deep networks and optimization techniques have been taken into account in this system. The proposed system is trained using a combination of Convolutional Neural Networks and Softmax classifier to extract features from localized regions of the input iris images. This is followed by classification into one out of 224 classes of the dataset. From the results, we conclude that the choice of hyperparameters and optimizers affects the efficiency of our proposed system. Our proposed approach outperforms existing approaches by attaining a high accuracy of 98 percent.