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

Sheng LI  Yong-fang YAO  Xiao-yuan JING  Heng CHANG  Shi-qiang GAO  David ZHANG  Jing-yu YANG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E92-D   No.12   pp.2527-2530
Publication Date: 2009/12/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E92.D.2527
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Pattern Recognition
Keyword: 
DCT frequency bands selection,  the improved KDCV,  nonlinear DCT feature extraction,  face recognition,  

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Summary: 
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.