Summary
International Technical Conference on Circuits/Systems, Computers and Communications
2016
Session Number:P3
Session:
Number:P3-10
Iris Feature Extraction using Local Thresholding with Variable Block Size
Ryo Ishikawa, Tomohiko Ohtsuka, Hiroyuki Aoki, Yuji Tateizumi ,
pp.1029-1032
Publication Date:2016/7/10
Online ISSN:2188-5079
Summary:
This paper presents a novel approach that uses local thresholding with an optimal block size to extract the features of the space domain from an image of the iris. The block size is selected optimally from two kinds, based on the variance of pixel intensity in the block of interest. The results of several experiments show that a complete separation of the matching intra-class and inter-class score distribution can be achieved. Furthermore, the equal error rate and false rejection rate achieved by using the proposed approach are 0.02% and 0.32%, respectively, thereby improving those obtained with the conventional approach, i.e., 0.89% and 24%, respectively.