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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1181

Title: Assembled matrix distance metric for 2DPCA-based face and palmprint recognition
Authors: Zuo, Wangmeng
Wang, Kuanquan
Zhang, David D.
Subjects: 2DPCA
Assemble matrix metric
Image recognition
Face recognition
Palmprint recognition
Issue Date: 2005
Publisher: IEEE
Citation: Proceedings of the 2005 International Conference on Machine Learning and Cybernetics : August 18-21, 2005, Guangzhou, China, p. 4870-4875.
Abstract: Two-dimensional Principal component analysis (2DPCA) is a novel image representation approach recently developed for image recognition. One advantage of 2DPCA is that it can extract feature matrix using a straightforward image projection technique. In this paper, we propose an assembled matrix distance metric (AMD) to measure the distance between two feature matrices. To test the efficiency of the proposed distance measure, we use two image databases, the ORL face and the PolyU palmprint. The experimental results show that the assembled matrix distance metric is very effective in 2DPCA based image recognition.
Rights: © 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Type: Conference Paper
URI: http://hdl.handle.net/10397/1181
ISBN: 0780390911
Appears in Collections:COMP Conference Papers & Presentations

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