Face recognition using local binary patterns with image Euclidean distance

Shihu Zhu; Zhen Song; Jufu Feng

doi:10.1117/12.750642

14 November 2007 Face recognition using local binary patterns with image Euclidean distance

Shihu Zhu, Zhen Song, Jufu Feng

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67904Z (2007) https://doi.org/10.1117/12.750642
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Shihu Zhu, Zhen Song, and Jufu Feng "Face recognition using local binary patterns with image Euclidean distance", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67904Z (14 November 2007); https://doi.org/10.1117/12.750642

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