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Wan, Minghua; Li, Ming; Yang, Guowei; Gai, Shan; Jin, Zhong
Information sciences, 08/2014, Letnik: 274Journal Article
In this paper we propose a novel method combining graph embedding and difference criterion techniques for image feature extraction, namely two-dimensional maximum embedding difference (2DMED). This method directly extracts the optimal projective vectors from 2D image matrices by simultaneously considering characteristic that is the intra-class compactness graph, the margin graph and inter-class separability graph, respectively. In this method, it is not necessary to convert the image matrix into high-dimensional image vector so that much computational time would be saved. In addition, the proposed method preserves the manifold reconstruction relationships in the low-dimensional subspace. Experimental results on the ORL, Yale face and USPS database show the effectiveness of the proposed method.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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