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  has been used to evaluate the performance of the proposed IRS. The experiments demonstrate that the proposed method gives better recognition rate compared to the LBP method. Experimental results show also that the proposed system especially the feature extraction method gives promising results.