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Robust iris recognition for local noise based on wavelet transforms  

Park Jonggeun (Department of electrical and electronic Engineering, Yonsei University)
Lee Chulhee (Department of electrical and electronic Engineering, Yonsei University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.42, no.2, 2005 , pp. 121-130 More about this Journal
Abstract
In this paper, we propose a feature extraction method for iris recognition using wavelet transforms. The wavelet transform is fast and has a good localization characteristic. In particular, the low frequency band can be used as an effective feature vector. In iris recognition, the noise caused by eyelid the eyebrow, glint, etc may be included in iris. The iris pattern is distorted by noises by itself, and a feature extraction algorithm based on filter such as Wavelets, Gabor transform spreads noises into whole iris region. Namely, such noises degrade the performance of iris recognition systems a major problem. This kind of noise has adverse effect on performance. In order to solve these problems, we propose to divide the iris image into a number of sub-region and apply the wavelet transform to each sub-region. Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform and region division noticeably improves recognition performance. However, it is noted that the processing time of the wavelet transform is much faster than that of the existing methods.
Keywords
생체 인식;홍채 인식;웨이블릿 변환;영역 분할;
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