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基于模糊集理论和细胞学习自动机的边缘检测器进行虹膜分割。

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

作者信息

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

机构信息

Soft Computing Research Group, Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia.

出版信息

Appl Opt. 2011 Jul 1;50(19):3191-200. doi: 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.

摘要

基于虹膜的生物识别系统根据个人虹膜的特征来识别个体,因为事实证明这些特征在很长一段时间内都是独一无二的。虹膜识别系统包括四个阶段,其中最重要的是预处理阶段,在该阶段进行虹膜分割。虹膜生物识别系统的准确性严重依赖于分割系统。本文提出了一种使用边缘检测技术和霍夫变换的虹膜分割系统。新提出的边缘检测系统以一种比其他传统虹膜分割方法更高效的方式提高了分割性能。

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