Face Recognition Based on Nonlinear DCT Discriminant Feature Extraction Using Improved Kernel DCV

被引:6
|
作者
Li, Sheng [1 ]
Yao, Yong-fang [1 ]
Jing, Xiao-yuan [1 ]
Chang, Heng [1 ]
Gao, Shi-qiang [1 ]
Zhang, David [2 ]
Yang, Jing-yu [3 ]
机构
[1] Nanjing Univ Posts & Telecommun, Nanjing 210003, Peoples R China
[2] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Hong Kong, Peoples R China
[3] Nanjing Univ Sci & Technol, Nanjing, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
DCT frequency bands selection; the improved KDCV; nonlinear DCT feature extraction; face recognition;
D O I
10.1587/transinf.E92.D.2527
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This letter proposes a nonlinear DCT discriminant feature extraction approach for face recognition. The proposed approach first selects appropriate DCT frequency bands according to their levels of nonlinear discrimination. Then, this approach extracts nonlinear discriminant features from the selected DCT bands by presenting a new kernel discriminant method, i.e. the improved kernel discriminative common vector (KDCV) method. Experiments on the public FERET database show that this new approach is more effective than several related methods.
引用
收藏
页码:2527 / 2530
页数:4
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