Abstract
This paper presents an effective system for recognizing the identity of a living person on the basis of iris patterns that is one of the physiological and biological features with high reliability. To represent the iris pattern efficiently, a new method for optimizing the dimension of feature vectors using wavelet transform is proposed. In order to increase the recognition accuracy of competitive learning algorithm, an efficient initialization of the weight vectors and a new method to determine the winner are also proposed. 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.
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Lim, S., Lee, K., Byeon, O., Kim, T. (2000). Effective Iris Recognition System by Optimized Feature Vectors and Classifier. In: Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2000. Lecture Notes in Computer Science, vol 1904. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45331-8_34
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DOI: https://doi.org/10.1007/3-540-45331-8_34
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