Iris Recognition Using Discrete Cosine Transform and Artificial Neural Networks | Zendy

Ahmad M. Sarhan | Zendy

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Iris Recognition Using Discrete Cosine Transform and Artificial Neural Networks

Author(s) -

Ahmad M. Sarhan

Publication year - 2009

Publication title -

journal of computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.161

H-Index - 28

eISSN - 1552-6607

pISSN - 1549-3636

DOI - 10.3844/jcssp.2009.369.373

Subject(s) - computer science , discrete cosine transform , artificial neural network , artificial intelligence , iris recognition , pattern recognition (psychology) , iris (biosensor) , computer vision , speech recognition , biometrics , image (mathematics)

Problem statement: This 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 designe

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