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Proceedings Paper

Infrared face recognition based on LBP histogram and KW feature selection
Author(s): Zhihua Xie
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Paper Abstract

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

Paper Details

Date Published: 21 August 2014
PDF: 6 pages
Proc. SPIE 9233, International Symposium on Photonics and Optoelectronics 2014, 92330B (21 August 2014); doi: 10.1117/12.2068131
Show Author Affiliations
Zhihua Xie, Jiangxi Science and Technology Normal Univ. (China)

Published in SPIE Proceedings Vol. 9233:
International Symposium on Photonics and Optoelectronics 2014
Zhiping Zhou, Editor(s)

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