Illumination Invariant Face Recognition

Computer Vision ◽

10.4018/978-1-5225-5204-8.ch003 ◽

2018 ◽

pp. 58-79 ◽

Cited By ~ 2

Author(s):

Chi Ho Chan ◽

Xuan Zou ◽

Norman Poh ◽

Josef Kittler

Keyword(s):

Face Recognition ◽

Visible Light ◽

Illumination Variation ◽

Illumination Invariant ◽

Illumination Problem ◽

Passive Techniques ◽

Face Appearance

Illumination variation is one of the well-known problems in face recognition, especially in uncontrolled environments. This chapter presents an extensive and up-to-date survey of the existing techniques to address this problem. This survey covers the conventional passive techniques that attempt to solve the illumination problem by studying the visible light images, in which face appearance has been altered by varying illumination, as well as the active techniques that aim to obtain images of face modalities invariant to environmental illumination.

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Illumination Invariant Face Recognition

Face Recognition in Adverse Conditions - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-4666-5966-7.ch007 ◽

2014 ◽

pp. 147-166 ◽

Cited By ~ 4

Author(s):

Chi Ho Chan ◽

Xuan Zou ◽

Norman Poh ◽

Josef Kittler

Keyword(s):

Face Recognition ◽

Visible Light ◽

Illumination Variation ◽

Illumination Invariant ◽

Illumination Problem ◽

Passive Techniques ◽

Face Appearance

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Diagonal Symmetric Pattern-Based Illumination Invariant Measure for Severe Illumination Variation Face Recognition

IEEE Access ◽

10.1109/access.2020.2983837 ◽

2020 ◽

Vol 8 ◽

pp. 63202-63213 ◽

Cited By ~ 1

Author(s):

Changhui Hu ◽

Fei Wu ◽

Jian Yu ◽

Xiaoyuan Jing ◽

Xiaobo Lu ◽

...

Keyword(s):

Face Recognition ◽

Invariant Measure ◽

Illumination Variation ◽

Illumination Invariant ◽

Symmetric Pattern

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Illumination invariant feature extraction and mutual-information-based local matching for face recognition under illumination variation and occlusion

Pattern Recognition ◽

10.1016/j.patcog.2011.03.012 ◽

2011 ◽

Vol 44 (10-11) ◽

pp. 2576-2587 ◽

Cited By ~ 22

Author(s):

Amirhosein Nabatchian ◽

Esam Abdel-Raheem ◽

Majid Ahmadi

Keyword(s):

Feature Extraction ◽

Face Recognition ◽

Mutual Information ◽

Illumination Variation ◽

Illumination Invariant ◽

Invariant Feature

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Efficient Gabor Phase Based Illumination Invariant for Face Recognition

Advances in Multimedia ◽

10.1155/2017/1356385 ◽

2017 ◽

Vol 2017 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Chunnian Fan ◽

Shuiping Wang ◽

Hao Zhang

Keyword(s):

Face Recognition ◽

Extraction Method ◽

Experimental Results ◽

Gabor Wavelet ◽

Image Transformation ◽

Face Database ◽

Illumination Variation ◽

Illumination Invariant ◽

Face Images

This paper presents a novel Gabor phase based illumination invariant extraction method aiming at eliminating the effect of varying illumination on face recognition. Firstly, It normalizes varying illumination on face images, which can reduce the effect of varying illumination to some extent. Secondly, a set of 2D real Gabor wavelet with different directions is used for image transformation, and multiple Gabor coefficients are combined into one whole in considering spectrum and phase. Lastly, the illumination invariant is obtained by extracting the phase feature from the combined coefficients. Experimental results on the Yale B and the CMU PIE face database show that our method obtained a significant improvement over other related methods for face recognition under large illumination variation condition.

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