Abstract

One of the most important authentication approaches is the iris recognition system (IRS), which is based on the iris of aperson for the authentication.In this paper, we propose a new iris recognition system using a novel feature extraction method. The proposed method, Neighborhood-based Binary Pattern, compares each neighbor of the central pixel withthe next neighbor to encode it by 1 if it is greater or 0 if it is lower than the central pixel. The obtained binary code is converted into a decimal number to construct the NBP image. In order to deal with the rotation problem, we propose an encoding process to obtain a rotation-invariant image. This image is subdivided into several blocks and the mean of each block is calculated. After, the variations of the means are encoded by a binary code. The obtained binary matrix is considered as feature descriptor of the iris. In the evaluation part, the CASIA iris database [10] has been used to evaluate the performance of the proposed IRS.

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