Boundary Localization of Non-ideal Iris Images Based on Nonlinear Gray-Level Transformation

Abstract

Boundary localization is one of the key issues in iris recognition system. For non-ideal iris images, some frequentlyoccurred cases such as dominant texture patterns, eyelashes or eyelids occlusions, low contrast between iris and sclera, and pupil deviation, will lead to inaccurate boundary localization. Specifically, if the intensive transition from iris to sclera is too smooth, outer boundary localization will be very difficult. To stress the problem, in this paper we propose the boundary localization method in which nonlinear gray-level transformation is innovated in outer boundary localization process. The experimental results depict that our algorithm have improved the localization accuracy for non-ideal iris compared to the classical algorithms