Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/224
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dc.contributorDepartment of Computing-
dc.creatorZhang, DDen_US
dc.creatorPeng, Hen_US
dc.creatorZhou, Jen_US
dc.creatorPal, SKen_US
dc.date.accessioned2014-12-11T08:27:08Z-
dc.date.available2014-12-11T08:27:08Z-
dc.identifier.issn1083-4427en_US
dc.identifier.urihttp://hdl.handle.net/10397/224-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2002 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.subjectDual eigenspaces methoden_US
dc.subjectEyes detectionen_US
dc.subjectFace recognitionen_US
dc.subjectHybrid neural methoden_US
dc.titleA novel face recognition system using hybrid neural and dual eigenspaces methodsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage787en_US
dc.identifier.epage793en_US
dc.identifier.volume32en_US
dc.identifier.issue6en_US
dc.identifier.doi10.1109/TSMCA.2003.808252en_US
dcterms.abstractIn this paper, we present an automated face recognition (AFR) system that contains two components: eye detection and face recognition. Based on invariant radial basis function (IRBF) networks and knowledge rules of facial topology, a hybrid neural method is proposed to localize human eyes and segment the face region from a scene. A dual eigenspaces method (DEM) is then developed to extract algebraic features of the face and perform the recognition task with a two-layer minimum distance classifier. Experimental results illustrate that the proposed system is effective and robust.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on systems, man, and cybernetics. Part A, Systems and humans, Nov. 2002, v. 32, no. 6, p. 787-793en_US
dcterms.isPartOfIEEE transactions on systems, man, and cybernetics. Part A, Systems and humansen_US
dcterms.issued2002-11-
dc.identifier.isiWOS:000180904400017-
dc.identifier.scopus2-s2.0-0036880614-
dc.identifier.rosgroupidr12711-
dc.description.ros2002-2003 > Academic research: refereed > Publication in refereed journal-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRA-
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryVoR alloweden_US
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