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Robust-to-rotation Iris Recognition Using Local Gradient Orientation Histogram  

Choi, Chang-Soo (충북대학교 전기전자컴퓨터공학부 컴퓨터공학과)
Jun, Byoung-Min (충북대학교 전기전자컴퓨터공학부)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.34, no.3C, 2009 , pp. 268-273 More about this Journal
Abstract
Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. In this paper, we propose a novel method based on local gradient orientation histogram which is robust to variations in illumination and rotations of iris patterns. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.
Keywords
Biometries; iris recognition; Gradient orientation; Orientation histogram; Iris rotation invariance;
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