Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/48555
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dc.contributor.authorAntón-Canalís, Luisen_US
dc.contributor.authorHernández Tejera, Marioen_US
dc.contributor.authorSánchez-Nielsen, Elenaen_US
dc.date.accessioned2018-11-23T22:50:42Z-
dc.date.available2018-11-23T22:50:42Z-
dc.date.issued2006en_US
dc.identifier.isbn978-3-540-44630-9en_US
dc.identifier.isbn3540446303
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10553/48555-
dc.description.abstractIn this paper, we present AddCanny, an Anisotropic Diffusion and Dynamic reformulation of the Canny edge detector. The proposal provides two modifications to classical Canny detector. The first one consists of using an anisotropic diffusion filter instead of a Gaussian filter as Canny does in order to obtain better edge detection and location. The second one is the replacement of the hysteresis step by a dynamic threshold process, in order to reduce blinking effect of edges during successive frames and, therefore, generate more stable edges in sequences. Also, a new performance measurement based on the Euclidean Distance Transform to evaluate the consistency of computed edges is proposed. The paper includes experimental evaluations with different video streams that illustrate the advantages of AddCanny compared to classical Canny edge detector.en_US
dc.languageengen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceBlanc-Talon J., Philips W., Popescu D., Scheunders P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelbergen_US
dc.subject1203 Ciencia de los ordenadoresen_US
dc.titleAddCanny: edge detector for video processingen_US
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.typeConferenceObjectes
dc.relation.conference8th International Conference on Advanced Concepts for Intelligent Vision Systems
dc.relation.conference8th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2006
dc.identifier.doi10.1007/11864349_46en_US
dc.identifier.scopus33750244963-
dc.identifier.isi000241489100046-
dc.contributor.authorscopusid8921191600-
dc.contributor.authorscopusid6508077539-
dc.contributor.authorscopusid13105159100-
dc.identifier.eissn1611-3349-
dc.description.lastpage512-
dc.description.firstpage501-
dc.relation.volume4179-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.contributor.daisngid3547239
dc.contributor.daisngid2188888
dc.contributor.daisngid1518383
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Anton-Canalis, L
dc.contributor.wosstandardWOS:Hernandez-Tejera, M
dc.contributor.wosstandardWOS:Sanchez-Nielsen, E
dc.date.coverdateEnero 2006
dc.identifier.conferenceidevents120527
dc.identifier.ulpgces
dc.description.ggs3
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.event.eventsstartdate18-09-2006-
crisitem.event.eventsstartdate18-09-2006-
crisitem.event.eventsenddate21-09-2006-
crisitem.event.eventsenddate21-09-2006-
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-
Colección:Actas de congresos
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