title: Iris segmentation using an edge detector based on fuzzy sets theory and cellular learning automata.
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.
authors: Soft Computing Research Group, Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia. afshin.ghanizadeh@gmail.com
authors: Afshin
authors: A
authors: Ghanizadeh
authors: Amir Atapour
authors: AA
authors: Abarghouei
authors: Saman
authors: S
authors: Sinaie
authors: Puteh
authors: P
authors: Saad
authors: Siti Mariyam
authors: SM
authors: Shamsuddin
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D007498:Iris / Q000033:anatomy & histology*; D010363:Pattern Recognition, Automated / Q000379:methods*