International Journal of Network Security & Its Applications (IJNSA)
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)
http://airccse.org/journal/ijnsa.html
Effectiveness of Feature Detectionoperators on the Performance of Iris Biometric Recognition System
Binsu C. Kovoor, Supriya M.H. and K. Poulose Jacob, Cochin University of Science and Technology, India
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%.
KEYWORDS
Iris, Canny, Daugman, Prewitt, Zero Cross, Sobel
Original Source URL: http://airccse.org/journal/nsa/5513nsa06.pdf
Volume Link: http://airccse.org/journal/jnsa13_current.html
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