Efficiency Improvement on Face Recognition using Gabor Tensor 


Vol. 35,  No. 9, pp. 748-755, Sep.  2010


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  Abstract

In this paper we propose an improved face recognition method using Gabor tensor. Gabor transform is known to be able to represent characteristic feature in face and reduced environmental influence. It may contribute to improve face recognition ratio. We attempted to combine three-dimensional tensor from Gabor transform with MPCA(Multilinear PCA) and LDA. MPCA with tensor which use various features is more effective than traditional one or two dimensional PCA. It is known to be robust to the change of face expression or light. Proposed method is simulated by MATALB9 using ORL and Yale face database. Test result shows that recognition ratio is improved maximum 9~27% compared with exisisting face recognition method.

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  Cite this article

[IEEE Style]

K. Park and H. Ko, "Efficiency Improvement on Face Recognition using Gabor Tensor," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 9, pp. 748-755, 2010. DOI: .

[ACM Style]

Kyung-jun Park and Hyung-hwa Ko. 2010. Efficiency Improvement on Face Recognition using Gabor Tensor. The Journal of Korean Institute of Communications and Information Sciences, 35, 9, (2010), 748-755. DOI: .

[KICS Style]

Kyung-jun Park and Hyung-hwa Ko, "Efficiency Improvement on Face Recognition using Gabor Tensor," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 9, pp. 748-755, 9. 2010.