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


Vol. 34,  No. 3, pp. 268-273, Mar.  2009


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  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.

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  Cite this article

[IEEE Style]

C. Choi and B. Jun, "Robust-to-rotation Iris Recognition Using Local Gradient Orientation Histogram," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 3, pp. 268-273, 2009. DOI: .

[ACM Style]

Chang-soo Choi and Byoung-min Jun. 2009. Robust-to-rotation Iris Recognition Using Local Gradient Orientation Histogram. The Journal of Korean Institute of Communications and Information Sciences, 34, 3, (2009), 268-273. DOI: .

[KICS Style]

Chang-soo Choi and Byoung-min Jun, "Robust-to-rotation Iris Recognition Using Local Gradient Orientation Histogram," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 3, pp. 268-273, 3. 2009.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880