Iris localization using local histogram and other image statistics

This paper presents an automatic method for iris localization based on image statistics. The proposed method localizes the iris in two stages. In the first stage, a circular moving window is used to localize the pupil by finding the range of grey levels that has the highest probability of enclosing the pupil. The window with the grey level peak having the minimum standard deviation of x- and y-coordinates is selected as the region enclosing the pupil. In the second stage, effect of the eyelashes is reduced by using median filtering and the iris boundary is estimated by taking the gradient of the rows within pupil. The proposed method has been tested on three public databases: CASIA-IrisV1, CASIA-IrisV3-Lamp and MMU version 1.0. Experimental results demonstrate the superiority of the proposed method in comparison with some of the existing methods.

► We have proposed an automatic iris localization method based on image statistics.
► Local histogram and standard deviation has been used for pupil localization.
► The use of partially overlapping circular window helps in better pupil localization.
► Gradient of the rows within the pupil region have been used for iris localization.
► Its performance does not degrade in case of partially opened eye images.