Evaluation of Iris Images Definition Based on Pupil's Edge Kurtosis

Abstract

In iris recognition system, the iris image definition is crucial to recognition effect. The blurred image may increase the rate of false rejection, and also increase the risk of error matching. This paper presents a fast and efficient method, which based on pupil's edge kurtosis, to value the definition of the iris images in this paper. The essential idea is to deny the point spread function (PSF) of an out-of-focus blur image from the line spread function (LSF). In a clear iris image, at least one sharp pupil's edge could be detected. Then, the LSF is constructed from the edge(s). This approach has fast speed as it works in spatial domain without complex Fourier transform or iterative computation. Moreover, through setting a generic criterion for blur measurement, it can be applied to different iris images without depending on the individual image contents. The experimental results validate the accuracy and efficiency of the proposed method.