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A robust iris localization method using an active contour model and hough transform

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

67 Scopus citations

Abstract

Iris segmentation is one of the crucial steps in building an iris recognition system since it affects the accuracy of the iris matching significantly. This segmentation should accurately extract the iris region despite the presence of noises such as varying pupil sizes, shadows, specular reflections and highlights. Considering these obstacles, several attempts have been made in robust iris localization and segmentation. In this paper, we propose a robust iris localization method that uses an active contour model and a circular Hough transform. Experimental results on 100 images from CASIA iris image database show that our method achieves 99% accuracy and is about 2.5 times faster than the Daugman's in locating the pupillary and the limbic boundaries.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2852-2856
Number of pages5
ISBN (Print)9780769541099
DOIs
StatePublished - 2010

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

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