Iris pattern recognition based on cumulative sums and majority vote methods

Abstract

Iris recognition is proving to be one of the most reliable biometric authentication systems. Since biometric authentication systems store multiple templates per user, there is need to optimize their computational and storage complexities by creating a single reliable specimen iris template per user. In this article, we propose two majority vote-based strategies for the creation of a single iris template per user. An algorithm based on cumulative-sums grey change analysis is used to extract the iris texture features for template creation. The experimental results on the CASIA and UBIRIS iris databases show that the approach is effective and efficient, with a recognition rate of 99.6%.