Iris Texture Characterization of Multi-Direction and Center-Symmetry Local Binary Pattern

In order to improve the iris texture characterization effect and obtain stable expression of local texture information, an iris texture characterization method based on multi-direction and center-symmetry local binary pattern is proposed. Firstly, a mask generated by quickly locating the edge of the eyelid is used to suppress the noise in the eyelid area. Secondly, on the basis of multi-direction, a proposed center-symmetry local binary pattern is used to characterize the iris texture. Finally, the shifting Hamming distance is used to determine whether the iris is matched or not. And specially to be mentioned is that the traditional correct recognition rate (CRR) is modified to deal with the shortcomings of the correct recognition rate evaluation index due to the imbalance of intra-class and inter-class matching times. The modified correct recognition rates obtained on CASIA.V1, CASIA.V3-Interval, JUL6.0 and CASIA.V4-Lamp libraries are 99.857%, 99.940%, 99.640% and 97.973%, respectively, and the equal error rate decreased by 0.03%‒5.96%. The experimental results show that the proposed algorithm can effectively characterize the iris texture information, and has good recognition performance and robustness. © 2023 Institute of Computing Technology. All rights reserved.