Localization of iris in gray scale images using intensity gradient

A new method of iris localization based on intensity value analysis is proposed in this paper. Iris recognition systems are mainly dependent on the performance of iris localization processing. Steps after localization involve normalization, feature extraction and matching. These steps are based on the accuracy and efficiency of localization of iris in human eye images. In the proposed scheme, the inner boundary of iris is calculated by finding the pupil center and radius using two methods. In the first method, selected region is adaptively binarized and centroid of the region utilized for obtaining pupil parameters. Edges are processed to detect radius and center of pupil during the second method. For outer iris boundary, a band is calculated within which iris outer boundary lies. Signals in one dimension are picked up along radial direction within determined band at different angles. Three points with maximum gradient are selected from each signal. Redundant points are deleted using Mahalanobis distance and remaining points are used to obtain the outer circle of the iris. Points for upper and lower eyelids are found in the same way as the iris outer boundary. Selected points are then statistically fitted to make parabolas and lastly eyelashes are removed from the image to completely localize the iris. Experimental results show that proposed method is very efficient and accurate.