Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1181
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dc.contributorDepartment of Computing-
dc.creatorZuo, W-
dc.creatorWang, K-
dc.creatorZhang, DD-
dc.date.accessioned2014-12-11T08:27:12Z-
dc.date.available2014-12-11T08:27:12Z-
dc.identifier.isbn0-7803-9091-1-
dc.identifier.urihttp://hdl.handle.net/10397/1181-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.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.en_US
dc.rightsThis 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.en_US
dc.subject2DPCAen_US
dc.subjectAssemble matrix metricen_US
dc.subjectImage recognitionen_US
dc.subjectFace recognitionen_US
dc.subjectPalmprint recognitionen_US
dc.titleAssembled matrix distance metric for 2DPCA-based face and palmprint recognitionen_US
dc.typeConference Paperen_US
dc.description.otherinformationAuthor name used in this publication: David Zhangen_US
dc.description.otherinformationBiometrics Research Centre, Department of Computingen_US
dcterms.abstractTwo-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.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProceedings of the 2005 International Conference on Machine Learning and Cybernetics : August 18-21, 2005, Guangzhou, China, p. 4870-4875-
dcterms.issued2005-
dc.identifier.scopus2-s2.0-28444476987-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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