30 October 2009 A weighted block-PCA infrared face recognition method based on blood perfusion image
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Proceedings Volume 7496, MIPPR 2009: Pattern Recognition and Computer Vision; 74961T (2009) https://doi.org/10.1117/12.831321
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
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.
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Zhihua Xie, Zhihua Xie, Guodong Liu, Guodong Liu, Shiqian Wu, Shiqian Wu, Zhijun Fang, Zhijun Fang, } "A weighted block-PCA infrared face recognition method based on blood perfusion image", Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74961T (30 October 2009); doi: 10.1117/12.831321; https://doi.org/10.1117/12.831321
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