Occlusion, reflections and iris shape deformations are the obstacles that stand in the way of a complete solution to iris localization problem. How to reject outliers caused by occlusion and reflections as much as possible before ellipse or spline fitting is a key challenge. For this reason, we proposed a Hough clustering method, which utilizes the shape configuration of iris edge points and their local appearance characteristics to distinguish iris from non-iris edge points. The experimental results show an improved localization performance of the proposed algorithm on CASIA2.0 and 3.0 databases.
Key words: Hough clustering, local edge point experts.
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