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http://dx.doi.org/10.5391/JKIIS.2003.13.6.673

Face Recognition Using Wavelet Coefficients and Hidden Markov Model  

Lee, Kyung-Ah (충북대학교 전기전자컴퓨터 공학부)
Lee, Dae-Jong (충북대학교 전기전자컴퓨터 공학부)
Park, Jang-Hwan (충주대학교 정보 제어 공학과)
Chun, Myung-Geun (충북대학교 전기전자컴퓨터 공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.13, no.6, 2003 , pp. 673-678 More about this Journal
Abstract
In this paper, we proposes a method for face recognition using HMM(hidden Markov model) and wavelet coefficients First, input images are compressed by using the multi-resolution analysis based on the discrete wavelet transform. And then, the wavelet coefficients obtained from each subband are used as feature vectors to construct the HMMs. In the recognition stage, we obtained higher recognition rate by summing of each recognition rate of wavelet subband. The usefulness of the proposed method was shown by comparing with conventional VQ and DCT-HMM ones. The experimental results show that the proposed method is more satisfactory than previous ones.
Keywords
HMM; Wavelet Coefficients;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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