A new approach to face recognition based on features fusion

DOI

10.2991/icecee-15.2015.261How to use a DOI?

Keywords

pattern recognition; two dimensional principal component (2DPCA); extended LBP

Abstract

In this paper, a theoretically efficient method is developed for face recognition. It is based on two dimensional principal component (2DPCA) analysis and extended local binary pattern (Extended LBP, ELBP) texture. First, the ELBP operator is employed to extract the local texture of the face images. Second, 2DPCA is used to reduce the dimensionality of the extracted feature and get the optimal projection space. Finally, the nearest distance classification is used to distinguish each testing image. The method has been ac-cessed on ATR-Jaffe and AR face databases. Results demonstrate that the proposed method is obviously superior to PCA and 2DPCA, and its recognition rate is more stable than PCA. Meanwhile, the proposed method has strong robustness against illumination and facial expression changes.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yanhong Fu
PY  - 2015/06
DA  - 2015/06
TI  - A new approach to face recognition based on features fusion
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 1398
EP  - 1404
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.261
DO  - 10.2991/icecee-15.2015.261
ID  - Fu2015/06
ER  -