Adaptive Iris Segmentation

Authors:
Rahib Abiyev;Kemal Kilic
Affiliations:
Dept. of Computer Engineering, Near East University, Nicosia, Cyprus;Dept. of Computer Engineering, Near East University, Nicosia, Cyprus
Venue:
ISA '09 Proceedings of the 3rd International Conference and Workshops on Advances in Information Security and Assurance
Year:
2009

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Abstract

In this paper an adaptive iris segmentation algorithm is presented. In the proposed algorithm Otsu Threshold value, average gray level of the image, image size, Hough-Circle search are used for adaptive segmentation of irises. Otsu threshold is used for selecting threshold value in order to determine pupil location. Then Hough circle is utilized for pupillary boundary, and finally gradient search is used for the limbic boundary detection. The algorithm achieved 98% segmentation rate in batch processing of the CASIA version 1 (756 Images) and version 3 (CASIA-IrisV3-Interval, 2655 Images) databases.