EXTRACTION OF TEXTURE FEATURES FROM LOCAL IRIS AREAS BY GLCM AND IRIS RECOGNITION SYSTEM BASED ON KNN

Year 2016, Volume: 6 Issue: 1, 44 - 52, 01.04.2016

Emrullah Acar

Abstract

Biometric systems are systems that enable individuals to be recognized in
electronic environment using some physical and behavioral characteristics.
Iris recognition system is one of the effective biometric recognition systems.
The main goal of this study is recognition of the human from the iris images
according to the local texture structures. The digital iris images were
derived from CASIA database. The texture features were extracted from the
four local iris regions of segmented image by using Gray Level CoOccurrence
Matrix (GLCM). Totally 88 parameters were extracted for each
image as a feature vector. Then, the obtained feature vectors were classified
by using k-Nearest Neighbor (k-NN) classifier and the average performance
of each system were compared according to different k values (1, 3, 5, 7 and
9). Finally, the best average performance among system architectures of iris
recognition system was observed as 85 % in k=1 neighbor structure of k-NN
classifier

Keywords

Systems, Iris Recognition, Image Processing, Classification, k-NN, GLCM