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

被引：11

作者：

Ghanizadeh, Afshin ^{[1
]}

Abarghouei, Amir Atapour ^{[1
]}

Sinaie, Saman ^{[1
]}

Saad, Puteh ^{[2
]}

Shamsuddin, Siti Mariyam ^{[1
]}

机构：

[1] Univ Teknol Malaysia, Fac Comp Sci & Informat Syst, Soft Comp Res Grp, Skudai 81310, Johor, Malaysia

[2] Univ Teknol Malaysia, Fac Comp Sci & Informat Syst, Dept Software Engn, Skudai 81310, Johor, Malaysia

来源：

APPLIED OPTICS | 2011年 / 50卷 / 19期

关键词：

RECOGNITION;

D O I：

10.1364/AO.50.003191

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

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. (C) 2011 Optical Society of America

引用

页码：3191 / 3200

页数：10

共 26 条

[1]

Amoroso S., 1971, Journal of Computer and System Sciences, V5, P455, DOI 10.1016/S0022-0000(71)80009-0

[2] Open synchronous cellular learning automata [J].