Model-based pupil and iris localization

Abstract

The iris is the most accurate biometric to date and its localization is a vital step in any iris recognition system. Iris localization can be considered as the search for the demarcation points, or step change in intensity at its boundaries. A failed localization will lead to incorrect iris segmentation and eventually to poor recognition. In the first stage, we proceed with the elimination of reflection and the reduction of lighting variations in eye images. In the second stage of our proposed system, radii and locations of the pupil and iris are obtained by maximizing the convolution of the image with a toroidal 2-D filtering shape derived from the Petrou-Kittler 1-D filter. Such a novel approach delivers robust localization of the inner and outer iris boundaries. We tested our system on a large dataset of poor quality eye images with substantial occlusions, illumination and defocus and the proposed algorithm is found to be robust and accurate.