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Optical Engineering

Fuzzy difference-of-Gaussian-based iris recognition method for noisy iris images
Author(s): Byung Jun Kang; Kang Ryoung Park; Jang-Hee Yoo; Kiyoung Moon
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Paper Abstract

Iris recognition is used for information security with a high confidence level because it shows outstanding recognition accuracy by using human iris patterns with high degrees of freedom. However, iris recognition accuracy can be reduced by noisy iris images with optical and motion blurring. We propose a new iris recognition method based on the fuzzy difference-of-Gaussian (DOG) for noisy iris images. This study is novel in three ways compared to previous works: (1) The proposed method extracts iris feature values using the DOG method, which is robust to local variations of illumination and shows fine texture information, including various frequency components. (2) When determining iris binary codes, image noises that cause the quantization error of the feature values are reduced with the fuzzy membership function. (3) The optimal parameters of the DOG filter and the fuzzy membership function are determined in terms of iris recognition accuracy. Experimental results showed that the performance of the proposed method was better than that of previous methods for noisy iris images.

Paper Details

Date Published: 1 June 2010
PDF: 10 pages
Opt. Eng. 49(6) 067001 doi: 10.1117/1.3447924
Published in: Optical Engineering Volume 49, Issue 6
Show Author Affiliations
Byung Jun Kang, Electronics and Telecommunications Research Institute (Korea, Republic of)
Kang Ryoung Park, Dongguk Univ. (Korea, Republic of)
Jang-Hee Yoo, Electronics and Telecommunications Research Institute (Korea, Republic of)
Kiyoung Moon, Electronics and Telecommunications Research Institute (Korea, Republic of)

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