Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/205
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dc.contributorDepartment of Computing-
dc.creatorKumar, Aen_US
dc.creatorZhang, DDen_US
dc.date.accessioned2014-12-11T08:23:38Z-
dc.date.available2014-12-11T08:23:38Z-
dc.identifier.isbn1424407281en_US
dc.identifier.urihttp://hdl.handle.net/10397/205-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 2007 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.subjectBiometricsen_US
dc.subjectHand geometryen_US
dc.subjectPersonal recognitionen_US
dc.subjectFeature representationen_US
dc.subjectFeature discretizationen_US
dc.titleBiometric recognition using entropy-based discretizationen_US
dc.typeConference Paperen_US
dc.description.otherinformationAuthor name used in this publication: Kumar, Ajayen_US
dcterms.abstractThe biometrics based recognition systems proposed in the literature have not yet exploited user-specific dependencies in the feature level representation. This paper suggests and investigates the performance improvement of the existing biometric systems using the discretization of extracted features. The performance improvement due to the unsupervised and supervised discretization schemes is compared on verity of classifiers; KNN, naïve Bayes, SVM and FFN. The experimental results on the hand-geometry database of 100 users achieve significant improvement in the recognition accuracy and confirm the usefulness of discretization in biometrics systems.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation2007 IEEE International Conference on Acoustics, Speech, and Signal Processing : proceedings : April 15-20, 2007, Hawaii, Convention Center, Honolulu, Hawaii, U.S.A., 2007, p. II125-II128en_US
dcterms.issued2007-
dc.identifier.isiWOS:000248908100032-
dc.identifier.scopus2-s2.0-34547501359-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRA-
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryVoR alloweden_US
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