Face illumination processing using nonlinear dynamic range adjustment and gradientfaces

DOI

10.2991/eeeis-16.2017.28How to use a DOI?

Keywords

Illumination Processing; Nonlinear Dynamic Range Adjustment; Gradientfaces; Face Recognition.

Abstract

In this paper, a novel illumination processing approach based on nonlinear dynamic range adjustment and gradientfaces is discussed. Firstly, the grayscale of face image is adjusted by nonlinear dynamic range adjustment using hyperbolic sine function in logarithm domain. After finishing the adjustment, gradientfaces is used to enhance the high frequency component of face image and extract distinguishing facial feature. Secondly, the data dimensionality is reduced by principal component analysis (PCA), the nearest neighbourhood-based classifier based on cosine distance is adopted for face classification. The experiment results on Yale-B frontal face database demonstrates that the average face recognition rate of our technique can reach to 99.74%. Therefore, it is insensitive to different lighting resources.

Copyright

© 2017, 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  - Zhi-Jun Yang
AU  - Xiang-Fei Nie
AU  - He Xue
AU  - Wen-Yi Xiong
PY  - 2016/12
DA  - 2016/12
TI  - Face illumination processing using nonlinear dynamic range adjustment and gradientfaces
BT  - Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
PB  - Atlantis Press
SP  - 202
EP  - 208
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-16.2017.28
DO  - 10.2991/eeeis-16.2017.28
ID  - Yang2016/12
ER  -