Rotation-invariant texture recognition

dc.contributor.authorMontoya Zegarra, Javier
dc.contributor.authorPaulo Papa, Joao
dc.contributor.authorLeite, Neucimar
dc.contributor.authorda Silva Torres, Ricardo
dc.contributor.authorFalcao, Alexandre
dc.date.accessioned2019-01-29T22:19:56Z
dc.date.available2019-01-29T22:19:56Z
dc.date.issued2007
dc.description.abstractThis paper proposes a new texture classification system, which is distinguished by: (1) a new rotation-invariant image descriptor based on Steerable Pyramid Decomposition, and (2) by a novel multi-class recognition method based on Optimum Path Forest. By combining the discriminating power of our image descriptor and classifier, our system uses small size feature vectors to characterize texture images without compromising overall classification rates. State-of-the-art recognition results are further presented on the Brodatz dataset. High classification rates demonstrate the superiority of the proposed method. © Springer-Verlag Berlin Heidelberg 2007.es_PE
dc.description.uriTrabajo académicoes_PE
dc.identifier.doihttps://doi.org/10.1007/978-3-540-76856-2_19es_PE
dc.identifier.isbnurn:isbn:9783540768555es_PE
dc.identifier.issn3029743es_PE
dc.identifier.urihttps://hdl.handle.net/20.500.12590/15910
dc.language.isoenges_PE
dc.publisherScopuses_PE
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-38149038001&partnerID=40&md5=fba3a1481de3f71fda7b80604208c844es_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.sourceRepositorio Institucional - UCSPes_PE
dc.sourceUniversidad Católica San Pabloes_PE
dc.sourceScopuses_PE
dc.subjectClassification (of information)es_PE
dc.subjectData structureses_PE
dc.subjectImage analysises_PE
dc.subjectImage descriptores_PE
dc.subjectOptimum Path Forestes_PE
dc.subjectSteerable Pyramid Decompositiones_PE
dc.subjectTexture classification systemes_PE
dc.subjectPattern recognitiones_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.02.00es_PE
dc.titleRotation-invariant texture recognitiones_PE
dc.typeinfo:eu-repo/semantics/article
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