A Comparative Study of Robust Segmentation Algorithms for Iris Verification System of High Reliability

Abstract

Abstract. Iris recognition is being widely used in different environments where the identity of a person is necessary. Therefore, it is a challenging problem to maintain high reliability and stability of this kind of systems in harsh environments. Iris segmentation is one of the most important process in iris recognition to preserve the above-mentioned characteristics. Indeed, iris segmentation may compromise the performance of the entire system. This paper presents a comparative study of four segmentation algorithms in the frame of the high reliability iris verification system. These segmentation approaches are implemented, evaluated and compared based on their accuracy using three unconstraint databases, one of them is a video iris database. The result shows that, for an ultra-high security system on verification at FAR = 0.01 %, segmentation 3 (Viterbi) presents the best results.