Human iris as a biometric for identity verification

The use of human biometrics for automatic identity verification has become widespread. Mostly used human biometrics are face, fingerprint, iris, gait, retina, voice, hand geometry etc. Among them iris is an externally visible, yet protected organ whose unique epigenetic pattern remains stable throughout one's whole life. These characteristics make it very attractive to use as a biometric for identifying individuals. This paper presents a detailed study of iris recognition technique. It encompasses an analysis of the reliability and the accuracy of iris as a biometric of person identification. The main phases of iris recognition are segmentation, normalization, feature encoding and matching. In this work automatic segmentation is performed using circular Hough transform method. Daugman's rubber sheet model is used in normalization process. Four level phase quantization based 1D Log-Gabor filters are used to encode the unique features of iris into binary template. And finally the Hamming distance is considered to examine the affinity of two templates in matching stage. We have experimented a better recognition result for CASIA-iris-v4 database.