Face Recognition Using LBP Eigenfaces

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...

Full description

Saved in:
Bibliographic Details
Published inIEICE Transactions on Information and Systems Vol. E97.D; no. 7; pp. 1930 - 1932
Main Authors LEI, Lei, KIM, Dae-Hwan, PARK, Won-Jae, KO, Sung-Jea
Format Journal Article
LanguageEnglish
Published The Institute of Electronics, Information and Communication Engineers 2014
Subjects
eigenfaces
face recognition
LBP
PCA
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:0916-8532
1745-1361
DOI:10.1587/transinf.E97.D.1930