文章基本信息

标题：Effectiveness of Feature Detectionoperators on the Performance of Iris Biometric Recognition System
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作者：Binsu C. Kovoor ; Supriya M.H. ; K. Poulose Jacob 等
期刊名称：International Journal of Network Security & Its Applications
印刷版ISSN：0975-2307
电子版ISSN：0974-9330
出版年度：2013
卷号：5
期号：5
DOI：10.5121/ijnsa.2013.550673
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person. Identification of this person is possible by applying appropriate matching algorithm.In this paper, Daugman's Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical analysis of different feature detection operators is performed, features extracted is encoded using Haar wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and False Reject Rate is 10%
关键词：Iris; Canny; Daugman; Prewitt; Zero Cross; Sobel