An Efficient Iris Segmentation Approach to Develop an Iris Recognition System

Iris recognition is regarded as the most stable and accurate biometric identification system. An iris recognition system basically consists of four stepssegmentation, normalization, encoding and matching. This paper proposes an efficient approach for iris segmentation. This segmentation approach uses a modified canny edge detection algorithm by considering gradient finding, nonmaximum suppression and hysteresis thresholding for the best results. This paper also present an automated iris recognition system based on proposed segmentation approach. This approach is proved to be very successful and about 95% images of dataset [CASIA database version 1.0] are segmented successfully. The iris recognition system resulted in False Reject Rates (FRR) and False Accept Rates (FAR) of 5.222 and 1.932 respectively.