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Proceedings Paper

Face recognition using local binary patterns with image Euclidean distance
Author(s): Shihu Zhu; Zhen Song; Jufu Feng
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Paper Abstract

Local Binary Pattern (LBP) feature to face recognition has been gaining interest lately. In this paper, a noval face recognition method based on Local Binary Pattern with Image Euclidean Distance(IMED) was proposed. IMED is first embedded in face images. Then a face image is divided into several blocks (facial regions) from which we extract local binary patterns and construct a global feature histogram that represents both the statistics of the facial micro-patterns and their spatial locations. At last, face recognition is performed using a nearest neighbor classifier in the computed feature space with Chi-Squared as a dissimilarity measure. Experiments show that IMED improve the performance of standard LBP algorithm.

Paper Details

Date Published: 14 November 2007
PDF: 7 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67904Z (14 November 2007); doi: 10.1117/12.750642
Show Author Affiliations
Shihu Zhu, Peking Univ. (China)
Zhen Song, Peking Univ. (China)
Jufu Feng, Peking Univ. (China)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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