Iris Texture Recognition Using Co-occurence Matrix Features with K_means Algorithm

Authors

  • Azhar M Kadim Department of Computer Science, Al-Nahrain University.

Keywords:

Iris recognition, Co-occurrence matrix, K_means, Feature extraction, Clustering

Abstract

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.

 

Published

2011-12-01

Issue

Section

Articles

How to Cite

(1)
Iris Texture Recognition Using Co-Occurence Matrix Features With K_means Algorithm. ANJS 2011, 14 (4), 185-190.