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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 50, Iss. 19 — Jul. 1, 2011
  • pp: 3191–3200

Iris segmentation using an edge detector based on fuzzy sets theory and cellular learning automata

Afshin Ghanizadeh, Amir Atapour Abarghouei, Saman Sinaie, Puteh Saad, and Siti Mariyam Shamsuddin  »View Author Affiliations


Applied Optics, Vol. 50, Issue 19, pp. 3191-3200 (2011)
http://dx.doi.org/10.1364/AO.50.003191


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Abstract

Iris-based biometric systems identify individuals based on the characteristics of their iris, since they are proven to remain unique for a long time. An iris recognition system includes four phases, the most important of which is preprocessing in which the iris segmentation is performed. The accuracy of an iris biometric system critically depends on the segmentation system. In this paper, an iris segmentation system using edge detection techniques and Hough transforms is presented. The newly proposed edge detection system enhances the performance of the segmentation in a way that it performs much more efficiently than the other conventional iris segmentation methods.

© 2011 Optical Society of America

OCIS Codes
(100.5010) Image processing : Pattern recognition
(100.4995) Image processing : Pattern recognition, metrics

ToC Category:
Image Processing

History
Original Manuscript: July 26, 2010
Revised Manuscript: December 1, 2010
Manuscript Accepted: January 12, 2011
Published: June 23, 2011

Citation
Afshin Ghanizadeh, Amir Atapour Abarghouei, Saman Sinaie, Puteh Saad, and Siti Mariyam Shamsuddin, "Iris segmentation using an edge detector based on fuzzy sets theory and cellular learning automata," Appl. Opt. 50, 3191-3200 (2011)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-50-19-3191

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