Face Recognition Using LBP Eigenfaces

Lei LEI  Dae-Hwan KIM  Won-Jae PARK  Sung-Jea KO  

IEICE TRANSACTIONS on Information and Systems   Vol.E97-D   No.7   pp.1930-1932
Publication Date: 2014/07/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E97.D.1930
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
LBP,  eigenfaces,  PCA,  face recognition,  

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In this paper, we propose a simple and efficient face representation feature that adopts the eigenfaces of Local Binary Pattern (LBP) space, referred to as the LBP eigenfaces, for robust face recognition. In the proposed method, LBP eigenfaces are generated by first mapping the original image space to the LBP space and then projecting the LBP space to the LBP eigenface subspace by Principal Component Analysis (PCA). Therefore, LBP eigenfaces capture both the local and global structures of face images. In the experiments, the proposed LBP eigenfaces are integrated into two types of classification methods, Nearest Neighbor (NN) and Collaborative Representation-based Classification (CRC). Experimental results indicate that the classification with the LBP eigenfaces outperforms that with the original eigenfaces and LBP histogram.