Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1211
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dc.contributorDepartment of Computing-
dc.creatorWu, X-
dc.creatorWang, K-
dc.creatorZhang, DD-
dc.date.accessioned2014-12-11T08:26:15Z-
dc.date.available2014-12-11T08:26:15Z-
dc.identifier.isbn1424406056-
dc.identifier.urihttp://hdl.handle.net/10397/1211-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 2006 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.subjectHamming distanceen_US
dc.subjectImage codingen_US
dc.subjectPixelsen_US
dc.subjectProgram processorsen_US
dc.titlePalmprint texture analysis using derivative of gaussian filtersen_US
dc.typeConference Paperen_US
dc.description.otherinformationAuthor name used in this publication: David Zhangen_US
dcterms.abstractThis paper presents a novel approach of palmprint texture analysis based on the derivative of gaussian filter. In this approach, the palmprint image is respectively preprocessed along horizontal and vertical direction using derivative of gaussian (DoG) Filters. And then the palmprint is encoded according to the sign of the value of each pixel of the filtered images. This code is called DoGCode of the palmprint. The size of DoGCode is 256 bytes. The similarity of two DoGCode is measured using their Hamming distance. This approach is tested on the PolyU Palmprint Database, which containing 7605 samples from 392 palms, and the EER is 0.19%, which is comparable with the existing palmprint recognition methods.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationCIS 2006 : 2006 International Conference on Computational Intelligence and Security : Guangzhou, China, November 3-6, 2006 : proceedings, v. 1, p. 751-754-
dcterms.issued2006-
dc.identifier.scopus2-s2.0-38549176659-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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