Ghanizadeh, A. and Abarghouei, A. A. and Sinaie, S. and Saad, Puteh and Shamsuddin, Siti Mariyam (2011) Iris segmentation using an edge detector based on fuzzy sets theory and cellular learning automata. Applied Optics, 50 (19). pp. 3191-3200. ISSN 1559-128X
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Official URL: http://dx.doi.org/10.1364/AO.50.003191
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.
Item Type: | Article |
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Uncontrolled Keywords: | detection system, fuzzy sets theory, iris recognition systems, iris segmentation |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Computer Science and Information System |
ID Code: | 29240 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 28 Feb 2013 00:08 |
Last Modified: | 25 Mar 2019 08:06 |
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