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Proceedings Paper

Face recognition based tensor structure
Author(s): De-qiang Yang; Zhi-xia Ye; Yang Zhao; Li-mei Liu
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Paper Abstract

Face recognition has broad applications, and it is a difficult problem since face image can change with photographic conditions, such as different illumination conditions, pose changes and camera angles. How to obtain some invariable features for a face image is the key issue for a face recognition algorithm. In this paper, a novel tensor structure of face image is proposed to represent image features with eight directions for a pixel value. The invariable feature of the face image is then obtained from gradient decomposition to make up the tensor structure. Then the singular value decomposition (SVD) and principal component analysis (PCA) of this tensor structure are used for face recognition. The experimental results from this study show that many difficultly recognized samples can correctly be recognized, and the recognition rate is increased by 9%-11% in comparison with same type of algorithms.

Paper Details

Date Published: 15 November 2011
PDF: 9 pages
Proc. SPIE 8335, 2012 International Workshop on Image Processing and Optical Engineering, 83350E (15 November 2011); doi: 10.1117/12.917596
Show Author Affiliations
De-qiang Yang, Yunnan Normal Univ. (China)
Zhi-xia Ye, Yunnan Normal Univ. (China)
Yang Zhao, Yunnan Normal Univ. (China)
Li-mei Liu, Yunnan Normal Univ. (China)

Published in SPIE Proceedings Vol. 8335:
2012 International Workshop on Image Processing and Optical Engineering
Hai Guo; Qun Ding, Editor(s)

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