Abstract
Iris location is a crucial step in iris recognition. Taking into consideration the fact that interior of the pupil, there would have some lighter spots because of reflection, this paper improves the commonly used coarse location method. It utilizes the gray scale histogram of the iris graphics, first computes the binary threshold, averaging the center of chords to coarsely estimate the center and radius of the pupil, and then finely locates it using the algorithm of circle detection in the binary graphic. This method could reduce the error of locating within the pupil. After that, this paper combines Canny edge detector and Hough voting mechanism to locate the outer boundary. Finally, a statistical method is exploited to exclude eyelash and eyelid areas. Experiments have shown the applicability and efficiency of this algorithm.
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© 2005 Springer-Verlag Berlin Heidelberg
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Sun, C., Zhou, C., Liang, Y., Liu, X. (2005). Study and Improvement of Iris Location Algorithm. In: Zhang, D., Jain, A.K. (eds) Advances in Biometrics. ICB 2006. Lecture Notes in Computer Science, vol 3832. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11608288_58
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DOI: https://doi.org/10.1007/11608288_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31111-9
Online ISBN: 978-3-540-31621-3
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