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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72694
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dc.contributor.authorOsaku, Daniel-
dc.contributor.authorMarana, Aparecido Nilceu-
dc.contributor.authorPapa, João Paulo-
dc.date.accessioned2014-05-27T11:26:01Z-
dc.date.accessioned2016-10-25T18:34:42Z-
dc.date.available2014-05-27T11:26:01Z-
dc.date.available2016-10-25T18:34:42Z-
dc.date.issued2011-09-26-
dc.identifierhttp://dx.doi.org/10.1007/978-3-642-24085-0_18-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 6978 LNCS, n. PART 1, p. 169-177, 2011.-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttp://hdl.handle.net/11449/72694-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72694-
dc.description.abstractThermal faceprint has been paramount in the last years. Since we can handle with face recognition using images acquired in the infrared spectrum, an unique individual's signature can be obtained through the blood vessels network of the face. In this work, we propose a novel framework for thermal faceprint extraction using a collection of graph-based techniques, which were never used to this task up to date. A robust method of thermal face segmentation is also presented. The experiments, which were conducted over the UND Collection C dataset, have showed promising results. © 2011 Springer-Verlag.en
dc.format.extent169-177-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectFaceprint-
dc.subjectImage Foresting Transform-
dc.subjectOptimum-Path Forest-
dc.subjectThermal Face Recognition-
dc.subjectData sets-
dc.subjectFace segmentation-
dc.subjectGraph-based-
dc.subjectGraph-based techniques-
dc.subjectImage foresting transforms-
dc.subjectInfrared spectrum-
dc.subjectRobust methods-
dc.subjectBlood vessels-
dc.subjectImage analysis-
dc.subjectSpectroscopy-
dc.subjectFace recognition-
dc.titleA graph-based framework for thermal faceprint characterizationen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationDepartment of Computing São Paulo State University - UNESP, Bauru-
dc.description.affiliationUnespDepartment of Computing São Paulo State University - UNESP, Bauru-
dc.identifier.doi10.1007/978-3-642-24085-0_18-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.identifier.scopus2-s2.0-80052972710-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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