Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44053
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dc.contributor.authorVargas, J. F.en_US
dc.contributor.authorTravieso, C. M.en_US
dc.contributor.authorAlonso, J. B.en_US
dc.contributor.authorFerrer, M. A.en_US
dc.date.accessioned2018-11-21T19:52:35Z-
dc.date.available2018-11-21T19:52:35Z-
dc.date.issued2010en_US
dc.identifier.isbn9780769542218en_US
dc.identifier.urihttp://hdl.handle.net/10553/44053-
dc.description.abstractA method for Off-line Handwritten Signature Verification is described. It works at the global and local image level, measuring the stroke gray-level variations by means of wavelet analysys and statistical texture features. This method begins with a proposed background removal. Then Wavelet Analysis allows to estimate and alleviate the global influence of ink-type, and finally, properties of the Co-occurrence Matrix are used as features representing individual characteristics at local level. Genuine samples have been used for train an SVM model, random and skilled forgeries have been used for testing it. Experiments were conducted on three differente databases (MCYT75, GPDS100, and GPDS750). Results are reasonable according to the state of the art and approaches that use the same public available database (MCYT75) and prove the feasibility of the proposed methodology.en_US
dc.languagespaen_US
dc.relation.ispartofProceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010en_US
dc.sourceProceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010 (5693627), p. 587-592en_US
dc.subject3307 Tecnología electrónicaen_US
dc.subject.otherForgery , Wavelet transforms , Wavelet analysis , Databases , Training , Matrix decomposition , Kernelen_US
dc.titleOff-line signature verification based on gray level information using wavelet transform and texture featuresen_US
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.typeConferenceObjectes
dc.relation.conference12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010
dc.identifier.doi10.1109/ICFHR.2010.96
dc.identifier.scopus79951701644-
dc.contributor.authorscopusid24767932500-
dc.contributor.authorscopusid6602376272-
dc.contributor.authorscopusid24774957200-
dc.contributor.authorscopusid55636321172
dc.contributor.authorscopusid55636321253-
dc.description.lastpage592-
dc.identifier.issue5693627-
dc.description.firstpage587-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.date.coverdateDiciembre 2010
dc.identifier.conferenceidevents121396
dc.identifier.ulpgces
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.event.eventsstartdate16-11-2010-
crisitem.event.eventsenddate18-11-2010-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0002-4621-2768-
crisitem.author.orcid0000-0002-7866-585X-
crisitem.author.orcid0000-0002-2924-1225-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameTravieso González, Carlos Manuel-
crisitem.author.fullNameAlonso Hernández, Jesús Bernardino-
crisitem.author.fullNameFerrer Ballester, Miguel Ángel-
Appears in Collections:Actas de congresos
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