Iris Texture Recognition Using Co-occurence Matrix Features with K_means Algorithm
Keywords:
Iris recognition, Co-occurrence matrix, K_means, Feature extraction, ClusteringAbstract
Iris Recognition is a rapidly expanding method of biometric authentication that is well suited to be applied to any access control system requiring high level of security. In this paper k-means algorithm is employed to optimize the database enrollment, this is carried out by choosing the best image (among many) for the same person to be a template in the database. Iris images are mapped into texture features produced from co-occurrence matrix. Experimental results show that the performance of the proposed recognition system gave true identification rate of about 86% when using optimized database and 59% when using selected database.
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Published
2011-12-01
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Articles
How to Cite
[1]
“Iris Texture Recognition Using Co-occurence Matrix Features with K_means Algorithm”, ANJS, vol. 14, no. 4, pp. 185–190, Dec. 2011, Accessed: May 02, 2024. [Online]. Available: https://anjs.edu.iq/index.php/anjs/article/view/786