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Proceedings Paper

A weighted block-PCA infrared face recognition method based on blood perfusion image
Author(s): Zhihua Xie; Guodong Liu; Shiqian Wu; Zhijun Fang
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Paper Abstract

In this paper, a novel method for infrared face recognition based on blood perfusion is proposed in this paper. Firstly, thermal images are converted into blood perfusion domain to enlarge between-class distance and lessen within-class distance, which makes full use of the biological feature of the human face. Based on the ratio of between-class distance to within-class distance (Ratio of Distance (RD)) in sub-blocks, block-PCA is utilized to get the local discrimination information, which can solve the small sample size problem (the null space problem). Finally, The FLD is applied to the holistic features combined by the extracted coefficients from the information of all sub-blocks. The experiments illustrate that the block-PCA+FLD doesn't discard the useful discriminant information in the holistic characters and the method proposed in this paper has better performance compared with traditional methods.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74961T (30 October 2009); doi: 10.1117/12.831321
Show Author Affiliations
Zhihua Xie, Jiangxi Sciences and Technology Normal Univ. (China)
Jiangxi Univ. of Finance and Economics (China)
Guodong Liu, Jiangxi Univ. of Finance and Economics (China)
Shiqian Wu, Jiangxi Univ. of Finance and Economics (China)
Zhijun Fang, Jiangxi Univ. of Finance and Economics (China)

Published in SPIE Proceedings Vol. 7496:
MIPPR 2009: Pattern Recognition and Computer Vision
Mingyue Ding; Bir Bhanu; Friedrich M. Wahl; Jonathan Roberts, Editor(s)

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