Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48554
DC FieldValueLanguage
dc.contributor.authorAntón-Canalís, Luisen_US
dc.contributor.authorHernández Tejera, Marioen_US
dc.contributor.authorSánchez-Nielsen, Elenaen_US
dc.date.accessioned2018-11-23T22:50:18Z-
dc.date.available2018-11-23T22:50:18Z-
dc.date.issued2007en_US
dc.identifier.isbn978-3-540-72846-7en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10553/48554-
dc.description.abstractThe Distance Transform is a powerful tool that has been used in many computer vision tasks. In this paper, the use of relevant maxima in distance transform's medial axis is proposed as a method for fast image data reduction. These disc-shaped maxima include morphological information from the object they belong to, and because maxima are located inside homogeneous regions, they also sum up chromatic information from the pixels they represent. Thus, maxima can be used instead of single pixels in algorithms which compute relations among pixels, effectively reducing computation times. As an example, a fast method for color image segmentation is proposed, which can also be used for textured zones detection. Comparisons with mean shift segmentation algorithm are shown.en_US
dc.languageengen_US
dc.relationTecnicas Para El Robustecimiento de Procesos en Vision Artificial Para la Interaccionen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceMartí J., Benedí J.M., Mendonça A.M., Serrat J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4477. Springer, Berlin, Heidelbergen_US
dc.subject1203 Ciencia de los ordenadoresen_US
dc.titleAnalysis of relevant maxima in distance transform: an application to fast coarse image segmentationen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference3rd Iberian Conference on Pattern Recognition and Image Analysis
dc.relation.conference3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007
dc.identifier.doi10.1007/978-3-540-72847-4_14en_US
dc.identifier.scopus38149004337-
dc.identifier.isi000247327500014-
dc.contributor.authorscopusid8921191600-
dc.contributor.authorscopusid6508077539-
dc.contributor.authorscopusid13105159100-
dc.identifier.eissn1611-3349-
dc.description.lastpage104-
dc.description.firstpage97-
dc.relation.volume4477-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.contributor.daisngid3547239
dc.contributor.daisngid2188888
dc.contributor.daisngid1518383
dc.identifier.eisbn978-3-540-72847-4-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Anton-Canalis, L
dc.contributor.wosstandardWOS:Hernandez-Tejera, M
dc.contributor.wosstandardWOS:Sanchez-Nielsen, E
dc.date.coverdateDiciembre 2007
dc.identifier.conferenceidevents120559
dc.identifier.ulpgces
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.project.principalinvestigatorLorenzo Navarro, José Javier-
crisitem.event.eventsstartdate06-06-2007-
crisitem.event.eventsstartdate06-06-2007-
crisitem.event.eventsenddate08-06-2007-
crisitem.event.eventsenddate08-06-2007-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Redes Neuronales, Aprendizaje Automático e Ingeniería de Datos-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0001-9717-8048-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameHernández Tejera, Francisco Mario-
Appears in Collections:Actas de congresos
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