Gabor-based multi-scale Illumination Normalization model for face recognition

机译：基于GABOR的面部识别多尺度照明标准化模型

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A novel Gabor-based Multi-scale Illumination Normalization (GMSIN) model is proposed and applied to face recognition. GMSIN uses Total variation under different norm constraints. It removes the lighting effect in two scale parts of image and fuses the multi-scaled illumination invariant features. Then a bank of Gabor filters is built to extract lighting invariant Gabor face representations. Finally the higher-order statistical relationships among variables of samples are extracted for classifier. According to the experiments on the large scale CAS-PEAL face database, GMSIN could outperform conventional algorithms when they face most outliers (lighting, expression, masking etc.).

机译：提出了一种新的基于GABOR的多尺度照明标准化（GMSIN）模型并应用于面部识别。 GMSIN在不同的规范约束下使用总变化。它在两个刻度部分中取消了照明效果，并融合了多级照明不变功能。然后建立了一系列Gabor过滤器，以提取照明不变的Gabor面部表示。最后提取样本变量之间的高阶统计关系，用于分类器。根据大规模CAS-PEAL面部数据库的实验，GMSIN可以在面对大多数异常值（照明，表达，遮蔽等）时优于传统算法。

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《International IEEE Conference on Intelligent Systems》|2008年||共4页
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中图分类 TP18-53;
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Image processing; face recognition; pattern recognition;

机译：图像处理;人脸识别;模式识别;

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3. An Improved Illumination Normalization and Robust Feature Extraction Technique for Face Recognition Under Varying Illuminations [J] . Yadav Jyotsna, Rajpal Navin, Mehta Rajesh Arabian Journal for Science and Engineering . 2019,第11期

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4. GABOR-BASED MULTI-SCALE ILLUMINATION NORMALIZATION MODEL FOR FACE RECOGNITION [C] . Jiying Wu, Gaoyun An, Qiuqi Kuan International Conference on Image Processing . 2008

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Gabor-based multi-scale Illumination Normalization model for face recognition

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