Iris recognition system using local features matching technique

Abstract

Iris is one of the most trustworthy biometric traits due to its stability and randomness. In this paper, the Iris Recognition System is developed with the intention of verifying both the uniqueness and performance of the human iris, as it is a briskly escalating way of biometric authentication of an individual. The proposed algorithm consists of an automatic segmentation system that is based on the Hough transform, and can localize the circular iris and pupil region, occluding eyelids and eyelashes, and reflections. The extracted iris region is then normalized into a rectangular block. Further, the texture features of normalized image are extracted using LBP (Local Binary Patterns). Finally, the Euclidean distance is employed for the matching process. In this thesis, the proposed system is tested with the co-operative database such as CASIA. With CASIA database, the recognition rate of proposed method is almost 91%, which shows the iris recognition system is reliable and accurate biometric technology.