Iris Feature Extraction and Recognition based on Gray Level Co-occurrence Matrix (GLCM) Technique
Author(s) -
A. Rabab
Publication year - 2018
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2018917826
Subject(s) - computer science , gray level , gray (unit) , artificial intelligence , pattern recognition (psychology) , iris (biosensor) , co occurrence matrix , iris recognition , feature extraction , computer vision , image (mathematics) , biometrics , image processing , medicine , image texture , radiology
Biometric features have received great attention for many applications. Iris recognition is one of the most modern biometric technique that is used for accurate and reliable authentication. Recently, Gray-Level Cooccurrence Matrix (GLCM) is one of the advanced techniques used for features extraction. In this paper, an iris recognition system proposed involves; preprocessing, feature extraction, and matching processes. After the preprocessing process, the feature extraction technique based on GLCM has been applied to pure iris region to extract features. Only one of the second-order statistical features known as contrast will be calculated from the generated co-occurrence matrix and stored it as a numerical feature vector in CASIA-v4.0-iris database. During recognition, the matching metric based on Euclidean distance has been used for authentication. Results have demonstrated (99.5%) highly accuracy rate with (0.02) FAR, and (0.01) FRR. General Terms Iris Recognition Technology and application of Iris Recognition Technology (authentication and security).
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