Iris Recognition Using Discrete Cosine Transform and Artificial Neural Networks
Abstract
Problem statement: The study presented an efficient Iris recognition system. Approach: The design used the discrete cosine transform for feature extraction and artificial neural networks for classification. The iris images used in this system were obtained from the CASIA database. Results: A robust system for iris recognition was developed. Conclusion: An iris recognition system that produces very low error rates was successfully designed.
DOI: https://doi.org/10.3844/jcssp.2009.369.373
Copyright: © 2009 Ahmad M. Sarhan. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- iris
- biometrics
- CASIA database
- cosine transform
- artificial neural networks
- feature extraction