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Iris recognition using multi-resolution transforms

Iris recognition using multi-resolution transforms Iris recognition is one of the most reliable personal identification methods and it plays a very important role in forensic and civilian applications. In this paper, an efficient multi-resolution based iris recognition system with high performance and less complexity is described. The system includes pre processing iris images, determining the pupil centre, converting the iris boundary to the stretched polar coordinate system, extracting the iris code based on texture analysis using multi-resolution transforms, such as Discrete Wavelet Transform (DWT), Double Density Wavelet Transform (DDWT) and Dual Tree Complex Wavelet Transform (DTCWT). A fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences in iris code is used for classification. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

Iris recognition using multi-resolution transforms

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2009.024273
Publisher site
See Article on Publisher Site

Abstract

Iris recognition is one of the most reliable personal identification methods and it plays a very important role in forensic and civilian applications. In this paper, an efficient multi-resolution based iris recognition system with high performance and less complexity is described. The system includes pre processing iris images, determining the pupil centre, converting the iris boundary to the stretched polar coordinate system, extracting the iris code based on texture analysis using multi-resolution transforms, such as Discrete Wavelet Transform (DWT), Double Density Wavelet Transform (DDWT) and Dual Tree Complex Wavelet Transform (DTCWT). A fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences in iris code is used for classification.

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2009

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