Improving the IRIS Recognition Under Different Illumination Using RETINEX Algorithms

Abstract

Iris detection and recognition provides more accurate and secure authentication nowadays. The probability of any two people having the same iris pattern is nearly zero, even the identical twins will not have the same iris pattern. The noise and illumination changes, challenges iris recognition correctness and security in authentication process. The available recent pre-processing techniques for iris detection address different type of noise suppression and removing unwanted information in iris, but still it strives with illumination issues. In this paper, we proposed Retinex algorithm for improving iris detection rate. The proposed work comprises into three steps: First we proposed Retinex algorithm in pre-processing, it works based on reflectance value of image and skips the illumination value in image, subsequently feature extraction uses Gabor filter for iris code generation. In conclusion, distance metrics Hamming distance used for iris recognition the proposed work evaluated MMU iris database under different illumination conditions and provides better results.