Improvement to libor masek algorithm of template matching method for iris recognition

Abstract

Iris recognition has become a popular research in recent years due to its reliability and nearly perfect recognition rates. Iris recognition system has three main stages: Image preprocessing, Feature extraction and Template matching. In the preprocessing stage, iris segmentation is critical to the success of subsequent feature extraction and template matching stages. Most recent algorithm on template matching proposed by Libor Masek shows an improvement of 3.6 % over existing algorithm like Hamming Distance. This paper addresses for improvement to Libor Masek algorithm of Template matching method for Iris Recognition. The method evaluates on iris images taken from the CASIA iris image database version 1.0 and version 3. Experimental results show that the proposed approach has more efficient than to Libor Masek in terms of Template matching Time of about 99%, Creation of template is of about 10 % and False Rejection Ratio (FRR) is of about 10 %.