A novel illumination normalization method in face recognition based on logarithmic total variation

2018 ◽  
Author(s):  
Yang Zhang ◽  
Changhui Hu ◽  
Xiaobo Lu ◽  
Jun Li
Keyword(s):  
Face Recognition ◽  
Total Variation ◽  
Normalization Method ◽  
Illumination Normalization

scholarly journals A Robust Illumination Normalization Method Based on Mean Estimation for Face Recognition

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yong Luo ◽  
Ye-Peng Guan ◽  
Chang-Qi Zhang
Keyword(s):  
Face Recognition ◽  
Estimation Method ◽  
Texture Features ◽  
Mean Value ◽  
Normalization Method ◽  
Illumination Normalization ◽  
Practical Applications ◽  
The Arts ◽  
Mean Estimation ◽  
The Impact

An illumination normalization method for face recognition has been developed since it was difficult to control lighting conditions efficiently in the practical applications. Considering that the irradiation light is of little variation in a certain area, a mean estimation method is used to simulate the illumination component of a face image. Illumination component is removed by subtracting the mean estimation from the original image. In order to highlight face texture features and suppress the impact of adjacent domains, a ratio of the quotient image and its modulus mean value is obtained. The exponent result of the ratio is closely approximate to a relative reflection component. Since the gray value of facial organs is less than that of the facial skin, postprocessing is applied to the images in order to highlight facial texture for face recognition. Experiments show that the performance by using the proposed method is superior to that of state of the arts.

Illumination Invariant Face Recognition Using Nonlocal Total Variation in Logarithmic Domain

2012 ◽  
Vol 241-244 ◽  
pp. 1652-1658 ◽  
Author(s):  
Cheng Zhe Xu
Keyword(s):  
Face Recognition ◽  
Total Variation ◽  
Facial Features ◽  
Face Database ◽  
Illumination Normalization ◽  
Illumination Invariant ◽  
Lighting Conditions ◽  
Total Variation Model ◽  
Nonlocal Total Variation ◽  
Robust Face Recognition

This paper presents a new illumination normalization method for robust face recognition under varying lighting conditions. In the proposed method, the illumination component is estimated by applying nonlocal total variation model in the logarithmic domain, and then the reflectance component is obtained based on reflectance model. The proposed method restrains the halo effect effectively while preserves the adequate texture information on the reflectance images. As an illumination invariant facial features, the reflectance images are directly utilized for face recognition. Experimental results on Yale face database B and CMU PIE database show that the performance of proposed method is robust and reliable in illumination invariant face recognition.

scholarly journals Total variation models for variable lighting face recognition

2006 ◽  
Vol 28 (9) ◽  
pp. 1519-1524 ◽  
Author(s):  
T. Chen ◽  
Wotao Yin ◽  
Xiang Sean Zhou ◽  
D. Comaniciu ◽  
T.S. Huang
Keyword(s):  
Face Recognition ◽  
Total Variation
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