期刊
NEUROCOMPUTING
卷 71, 期 16-18, 页码 3534-3543出版社
ELSEVIER
DOI: 10.1016/j.neucom.2007.09.013
关键词
Supervised linear dimensionality reduction; Face difference model; Discriminant projection embedding; Face recognition; Palmprint recognition
资金
- National Natural Science Foundation (NNSF) [60573148]
- Specialized Research Fund for the Doctoral Program of Higher Education [SRFDP-20060003102]
In this paper, we propose a new supervised linear dimensionality reduction method called discriminant projection embedding (DPE). DPE can preserve within-class neighboring geometry and extract between-class relevant structures for classification effectively. The proposed method is applied to face and palmprint recognition and is examined using the AR and FERET face databases and the PolyU palmprint database. Experimental results show that DPE consistently outperforms other up-to-date supervised linear dimensionality reduction methods when the training sample size per class is small. This demonstrates the effectiveness and robustness of DPE. (C) 2007 Elsevier B.V. All rights reserved.
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