Feature facial image recognition using VQ histogram in the DCT domain

Qiu Chen; Koji Kotani; Feifei Lee; Tadahiro Ohmi

doi:10.1117/12.855647

26 February 2010 Feature facial image recognition using VQ histogram in the DCT domain

Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi

Proceedings Volume 7546, Second International Conference on Digital Image Processing; 75460J (2010) https://doi.org/10.1117/12.855647
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore

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.

Citation Download Citation

Qiu Chen, Koji Kotani, Feifei Lee, and Tadahiro Ohmi "Feature facial image recognition using VQ histogram in the DCT domain", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75460J (26 February 2010); https://doi.org/10.1117/12.855647

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