A novel local illumination normalization approach for face recognition

Authors:
Zhichao Lian;Meng Joo Er;Juekun Li
Affiliations:
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Year:
2011

Citing 5
Cited 0

Face Recognition: The Problem of Compensating for Changes in Illumination Direction

IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose

IEEE Transactions on Pattern Analysis and Machine Intelligence
Acquiring Linear Subspaces for Face Recognition under Variable Lighting

IEEE Transactions on Pattern Analysis and Machine Intelligence
An efficient illumination normalization method for face recognition

Pattern Recognition Letters
Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, different from most of existing methods, an additive term as noise is considered in the proposed method besides a multiplicative illumination term in the illumination model. Discrete cosine transform coefficients of high frequency band are discarded to eliminate the effect caused by noise. Based on local characteristic of human face, a simple but effective illumination normalization method local relation map is proposed. The experimental results on the Yale B and Extended Yale B prove the outperformance and lower computational burden of the proposed method compared to other existing methods.