Face recognition in complex lighting environment

被引：0

作者：

Zou, ChangPeng ^{[1
]}

Ni, ChengGong ^{[1
]}

Lin, Qing ^{[1
]}

Feng, KaiQiang ^{[1
]}

Wang, YuXi ^{[1
]}

机构：

[1] Jiangsu Univ, Sch Comp Sci & Telecommun Engn, Zhenjiang 212013, Jiangsu, Peoples R China

来源：

2019 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY (CYBERC) | 2019年

关键词：

Image processing; face recognition; feature fusion; local binary mode; SCALE;

D O I：

10.1109/CyberC.2019.00037

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In view of the non-linear change of face image caused by illumination, the recognition rate is reduced and the ability of single feature expression is limited. Based on local binary mode (LBP) and Gabor wavelet, we propose a face recognition method. By extracting these two local features which are robust to illumination, we use generalized discriminant analysis (GDA) to reduce the dimension and then use discriminant correlation analysis (DCA) to fuse the features. Experiments on the ORL, Extended YaleB, OFD, and CAS-PEAL face databases demonstrate that the proposed method works better than LBP or Gabor alone.

引用

页码：162 / 165

页数：4

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