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

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.