A Fast and Accurate Optimized Iris Recognition Scheme Based on a Modified GSO Algorithm

Recently., through the messy events that happen in the world, many people have been threatened by various terrorist assaults. Therefore, there is a need to provide various intelligent techniques for recognizing and diminishing these attacks reasonably. Biometric traits are considered one of the essential resources for these techniques. Among all the biometric traits, iris recognition has emerged as the most stable, reliable, low-cost, and distinct scheme for identifying or verifying people. Although many techniques in this field have been proposed, several issues still require solving, such as time-consuming and accuracy. In this paper, in order to handle these issues, an efficient iris recognition scheme depending on one of the common modern swarm intelligence algorithms has been proposed. Modified Glowworm Swarm Optimization (GSO) is employed for extracting optimal features from the iris with high efficiency in the optimization function. This employed optimization algorithm reduces the feature space dimensionality and the actual time needed for recognizing the human iris. The results show that the proposed recognition scheme has achieved higher accuracy using the IIT -Delhi dataset.