Evolution of performance analysis of Iris recognition system by using hybrid methods of feature extraction and matching by hybrid classifier for iris recognition system

In today's world the higher stable and distinct biometric characteristics to identify and / or to verify any person are the human iris. Iris recognition system consists image acquisition, localization, normalization, features extraction and matching. Iris images are taken from CASIA iris VI database for study. In this paper we make a comparative study of performance of image transform using Haar transform, PCA, Block sum algorithm and hybrid algorithm for iris verification to extract features on specific portion of the iris for improving the performance of an iris recognition system. The hybrid methods are evaluated by combining Haar transform and block sum algorithm. The classifiers used in this study are hybrid classifier i.e. ANN and FAR/FRR and the experimental results show that this technique produces good performance on CASIA VI iris database.