Kernel Discriminant Embedding in face recognition


Han, Pang Ying and Jin, Andrew Teoh Beng and Toh Kar, Ann (2011) Kernel Discriminant Embedding in face recognition. Journal of Visual Communication and Image Representation, 22 (7). pp. 634-642. ISSN 10473203

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In this paper, we present a novel and effective feature extraction technique for face recognition. The proposed technique incorporates a kernel trick with Graph Embedding and the Fisher's criterion which we call it as Kernel Discriminant Embedding (KDE). The proposed technique projects the original face samples onto a low dimensional subspace such that the within-class face samples are minimized and the between-class face samples are maximized based on Fisher's criterion. The implementation of kernel trick and Graph Embedding criterion on the proposed technique reveals the underlying structure of data. Our experimental results on face recognition using ORL, FRGC and FERET databases validate the effectiveness of KDE for face feature extraction. (C) 2011 Elsevier Inc. All rights reserved.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 09 Jan 2012 04:01
Last Modified: 09 Jan 2012 04:01


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