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Proceedings Paper

Feature facial image recognition using VQ histogram in the DCT domain
Author(s): Qiu Chen; Koji Kotani; Feifei Lee; Tadahiro Ohmi
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Paper Abstract

In this paper, a novel algorithm using vector quantization (VQ) method for facial image recognition in DCT domain is presented. Firstly, feature vectors of facial image are generated by using DCT (Discrete Cosine transform) coefficients in low frequency domains. Then codevector referred count histogram, which is utilized as a very effective personal feature value, is obtained by Vector Quantization (VQ) processing. Publicly available AT&T database of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions, is used to evaluate the performance of the proposed algorithm. Experimental results show face recognition using proposed feature vector is very efficient. The highest average recognition rate of 94.8% is obtained.

Paper Details

Date Published: 26 February 2010
PDF: 7 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75460J (26 February 2010); doi: 10.1117/12.855647
Show Author Affiliations
Qiu Chen, Tohoku Univ. (Japan)
Koji Kotani, Tohoku Univ. (Japan)
Feifei Lee, Tohoku Univ. (Japan)
Tadahiro Ohmi, Tohoku Univ. (Japan)

Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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