Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43962
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dc.contributor.authorFerrer, Miguel A.en_US
dc.contributor.authorAlonso, Jesus B.en_US
dc.contributor.authorDavid, Sebastienen_US
dc.contributor.authorTravieso, Carlos M.en_US
dc.date.accessioned2018-11-21T19:11:33Z-
dc.date.available2018-11-21T19:11:33Z-
dc.date.issued2015en_US
dc.identifier.isbn9783200001657en_US
dc.identifier.issn2219-5491en_US
dc.identifier.urihttp://hdl.handle.net/10553/43962-
dc.description.abstractIn computer vision, two-dimensional shape classification is a complex and well known topic, often basic for three-dimensional object recognition. Among different classification methods, this paper is focus on those that describe the 2D shape by means of a sequence of d-dimensional vectors which feeds a left to right hidden Markov model (HMM) recogniser. We propose a methodology for featuring the 2D shape with a sequence of vectors that take advantage of the HMM ability to spot the times when the infrequent vectors of the input sequence of vectors occur. This propierty is deduced by the repetition of the same HMM state during the moments in which the infrequent vectors is repeated. These HMM states are called by us synchronism states. The synchronization between the HMM and the input sequence of vectors can be improved thanks to adding an index component to the vectors. We show the recognition rate improvement of our proposal on selected applicationsen_US
dc.languagespaen_US
dc.publisher2219-5491en_US
dc.relation.ispartofEuropean Signal Processing Conferenceen_US
dc.sourceEuropean Signal Processing Conference[ISSN 2219-5491],v. 06-10-September-2004 (7079990), p. 761-764en_US
dc.subject3307 Tecnología electrónicaen_US
dc.subject.otherHidden Markov models , Synchronization , Abstracts , Pattern recognition , Shape , Tutorials , NISTen_US
dc.titleParameterization methodology for 2D shape classification by hidden Markov modelsen_US
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.typeConferenceObjectes
dc.relation.conference12th European Signal Processing Conference, EUSIPCO 2004
dc.identifier.scopus84979897047-
dc.contributor.authorscopusid55636321172-
dc.contributor.authorscopusid24774957200-
dc.contributor.authorscopusid57190423043-
dc.contributor.authorscopusid6602376272-
dc.description.lastpage764-
dc.identifier.issue7079990-
dc.description.firstpage761-
dc.relation.volume06-10-September-2004-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.date.coverdateAbril 2015
dc.identifier.conferenceidevents121584
dc.identifier.ulpgces
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptIDeTIC: 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.deptIDeTIC: 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.deptIDeTIC: 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.orcid0000-0002-2924-1225-
crisitem.author.orcid0000-0002-7866-585X-
crisitem.author.orcid0000-0002-4621-2768-
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.fullNameFerrer Ballester, Miguel Ángel-
crisitem.author.fullNameAlonso Hernández, Jesús Bernardino-
crisitem.author.fullNameTravieso González, Carlos Manuel-
crisitem.event.eventsstartdate06-09-2004-
crisitem.event.eventsenddate10-09-2004-
Appears in Collections:Actas de congresos
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