Study and improvement of iris location algorithm

10Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

This article is free to access.

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. © Springer-Verlag Berlin Heidelberg 2005.

Cite

CITATION STYLE

APA

Sun, C., Zhou, C., Liang, Y., & Liu, X. (2006). Study and improvement of iris location algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3832 LNCS, pp. 436–442). https://doi.org/10.1007/11608288_58

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free