Efficient Iris Recognition through Improvement of Feature Vector and Classifier

In this paper, we propose an efficient method for personal identification by analyzing iris patterns that have a high level of stability and distinctiveness. To improve the efficiency and accuracy of the proposed system, we present a new approach to making a feature vector compact and efficient by u...

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Bibliographic Details
Published in:ETRI journal 2001-06, Vol.23 (2), p.61-70
Main Authors: Lim, Shinyoung, Lee, Kwanyong, Byeon, Okhwan, Kim, Taiyun
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Exact sciences and technology
Image processing
Information, signal and communications theory
Pattern recognition. Digital image processing. Computational geometry
Signal processing
Telecommunications and information theory
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Summary:In this paper, we propose an efficient method for personal identification by analyzing iris patterns that have a high level of stability and distinctiveness. To improve the efficiency and accuracy of the proposed system, we present a new approach to making a feature vector compact and efficient by using wavelet transform, and two straightforward but efficient mechanisms for a competitive learning method such as a weight vector initialization and the winner selection. With all of these novel mechanisms, the experimental results showed that the proposed system could be used for personal identification in an efficient and effective manner.
ISSN:1225-6463
2233-7326
DOI:10.4218/etrij.01.0101.0203