Iris Segmentation using an Edge Detector based on Fuzzy Sets Theory and Cellular Learning Automata

Ghanizadeh, Afshin; Atapour-Abarghouei, Amir; Sinaie, Saman; Saad, Puteh; Shamsuddin, Siti Mariyam

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.

Citation

Ghanizadeh, A., Atapour-Abarghouei, A., Sinaie, S., Saad, P., & Shamsuddin, S. M. (2011). Iris Segmentation using an Edge Detector based on Fuzzy Sets Theory and Cellular Learning Automata. Applied Optics, 50(19), 3191-3200. https://doi.org/10.1364/ao.50.003191

• Journal Article Type: Article
• Acceptance Date: Jan 12, 2011
• Online Publication Date: Jun 23, 2011
• Publication Date: 2011-07
• Deposit Date: Oct 13, 2017
• Journal: Applied Optics
• Print ISSN: 1559-128X
• Electronic ISSN: 2155-3165
• Publisher: Optica
• Peer Reviewed: Peer Reviewed
• Volume: 50
• Issue: 19
• Pages: 3191-3200
• DOI: https://doi.org/10.1364/ao.50.003191
• Public URL: https://durham-repository.worktribe.com/output/1373880