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Research Article

Method for Face Image Dimension Reduction Based on the Symmetrical Characteristics of Face

Zeng Yue, Wu Qiao and He Xinzhou
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For using more covariance information lost by 2DPCA (two dimension principal component analysis). Research on method for face image dimension reduction based on the symmetrical characteristics of face (DRVS) is proposed, which can use the most covariance information of half a face image. After a lot of in ORL and YALE experimental research, it shows that DRVS is more reliable and highly efficient and is also superior to the traditional algorithm (ICA, eigenfaces and Kernel eigenfaces).

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  How to cite this article:

Zeng Yue, Wu Qiao and He Xinzhou, 2013. Method for Face Image Dimension Reduction Based on the Symmetrical Characteristics of Face. Journal of Applied Sciences, 13: 3245-3250.

DOI: 10.3923/jas.2013.3245.3250


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