Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/220
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dc.contributorDepartment of Computing-
dc.creatorPathak, AK-
dc.creatorZhang, DD-
dc.date.accessioned2014-12-11T08:27:09Z-
dc.date.available2014-12-11T08:27:09Z-
dc.identifier.issn1057-7149-
dc.identifier.urihttp://hdl.handle.net/10397/220-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_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.subjectBiometricsen_US
dc.subjectFeature level fusionen_US
dc.subjectFeature subset selection and combinationen_US
dc.subjectHand-shape recognitionen_US
dc.subjectPalmprint recognitionen_US
dc.titlePersonal recognition using hand shape and textureen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationAuthor name used in this publication: Ajay Kumaren_US
dc.identifier.spage2454-
dc.identifier.epage2461-
dc.identifier.volume15-
dc.identifier.issue8-
dc.identifier.doi10.1109/TIP.2006.875214-
dcterms.abstractThis paper proposes a new bimodal biometric system using feature-level fusion of hand shape and palm texture. The proposed combination is of significance since both the palmprint and hand-shape images are proposed to be extracted from the single hand image acquired from a digital camera. Several new hand-shape features that can be used to represent the hand shape and improve the performance are investigated. The new approach for palmprint recognition using discrete cosine transform coefficients, which can be directly obtained from the camera hardware, is demonstrated. None of the prior work on hand-shape or palmprint recognition has given any attention on the critical issue of feature selection. Our experimental results demonstrate that while majority of palmprint or hand-shape features are useful in predicting the subjects identity, only a small subset of these features are necessary in practice for building an accurate model for identification. The comparison and combination of proposed features is evaluated on the diverse classification schemes; naive Bayes (normal, estimated, multinomial), decision trees (C4.5, LMT), k-NN, SVM, and FFN. Although more work remains to be done, our results to date indicate that the combination of selected hand-shape and palmprint features constitutes a promising addition to the biometrics-based personal recognition systems.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on image processing, Aug. 2006, v. 15, no. 8, p.2454-2461-
dcterms.isPartOfIEEE transactions on image processing-
dcterms.issued2006-08-
dc.identifier.isiWOS:000239286900032-
dc.identifier.scopus2-s2.0-33746265519-
dc.identifier.pmid16900698-
dc.identifier.eissn1941-0042-
dc.identifier.rosgroupidr30284-
dc.description.ros2006-2007 > Academic research: refereed > Publication in refereed journal-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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