Reducing the effect of partial occlusions on IRIS recognition

Abstract

The difficulty in the process of human identification by iris recognition is that the iris images captured may have occlusions by the eyelids and eyelashes. In that case, recognition of occluded iris patterns becomes hard and the corresponding person may not be correctly recognized. In order to reduce the effect of eyelid or eyelash occlusion on the recognition of human beings by their iris patterns, we propose a simple and efficient method for iris recognition using specific regions on the iris images without using the traditional preprocessing approach before applying the feature extraction method to recognize the irises. First of all these regions are individually experimented and then the outputs of each region are combined using a multiple classifier combination method with the feature extraction method Principal Component Analysis (PCA). The experiments on the iris images, with and without occlusions, demonstrate that the proposed approach achieves better recognition rates compared to the recognition rates of the holistic approaches.