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A SVM based iris recognition using wavelet packet transform and manhattan distance
Published in International Journal of Scientific and Technology Research
2020
Volume: 9
   
Issue: 2
Pages: 6232 - 6236
Abstract
The high security necessities in work and management motivated prospering of biometric technologies. Currently iris recognition is largely endorsed system. An expanding biometric identification technique which offers distinct verification based on distinguishing feature or characteristic possessed by the individual. Here, a fast methodology for classification and identification is suggested. The proposed system advances the effectiveness of iris recognition system. A joint tactic of SVM-Distance matching along with HAAR wavelet packet transform for feature extraction is used. For iris detection, Hough transform and Doughman's rubber sheet model for normalization is used. As in multi-faceted iris pattern, most of the information lies within zigzag collarette area, it is chosen for feature extraction. The proposed method shows a trade-off between two approaches SVM-HD and SVM-MD in terms of recognition accuracy and execution time. Maximum accuracy rate of 99.72% is achieved on CASIAV1.0 database. © 2020 IJSTR.
About the journal
JournalInternational Journal of Scientific and Technology Research
PublisherInternational Journal of Scientific and Technology Research
ISSN22778616