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Please use this identifier to cite or link to this item: http://purl.org/purl/3904

Title: Effectiveness Of Feature Detection Operators On The Performance Of Iris Biometric Recognition System
Authors: Poulose Jacob,K
Binsu, Kovoor C
Supriya, M H
Keywords: Iris
Canny
Daugman
Prewitt
Zero Cross
Sobel
Issue Date: 2013
Publisher: International Journal
Abstract: 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%.
Description: International Journal of Network Security & Its Applications (IJNSA), Vol.5, No.5, September 2013
URI: http://dyuthi.cusat.ac.in/purl/3904
Appears in Collections:Dr. K Poulose Jacob

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