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dc.creatorCerman, Martines
dc.creatorJanusch, Ineses
dc.creatorGonzález Díaz, Rocíoes
dc.creatorKropatsch, Walter G.es
dc.date.accessioned2021-10-18T10:12:12Z
dc.date.available2021-10-18T10:12:12Z
dc.date.issued2016
dc.identifier.citationCerman, M., Janusch, I., González Díaz, R. y Kropatsch, W.G. (2016). Topology-based image segmentation using LBP pyramids. Machine Vision and Applications, 27 (8), 1161-1174.
dc.identifier.issn0932-8092es
dc.identifier.urihttps://hdl.handle.net/11441/126666
dc.description.abstractIn this paper, we present a new image segmentation algorithmwhich is based on local binary patterns (LBPs) and the combinatorial pyramid and which preserves structural correctness and image topology. For this purpose, we define a codification of LBPs using graph pyramids. Since the LBP code characterizes the topological category (local max, min, slope, saddle) of the gray level landscape around the center region, we use it to obtain a “minimal” image representation in terms of the topological characterization of a given 2D grayscale image. Based on this idea, we further describe our hierarchical texture aware image segmentation algorithm and compare its segmentation output and the “minimal” image representation.es
dc.description.sponsorshipMinisterio de Economía y Competitividad MTM2015-67072-Pes
dc.formatapplication/pdfes
dc.format.extent14es
dc.language.isoenges
dc.publisherSpringeres
dc.relation.ispartofMachine Vision and Applications, 27 (8), 1161-1174.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectLocal binary patternses
dc.subjectIrregular graph pyramides
dc.subjectPrimal and dual graphes
dc.subjectTopological characterizationes
dc.subjectImage segmentationes
dc.titleTopology-based image segmentation using LBP pyramidses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Matemática Aplicada I (ETSII)es
dc.relation.projectIDMTM2015-67072-Pes
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s00138-016-0795-1es
dc.identifier.doi10.1007/s00138-016-0795-1es
dc.journaltitleMachine Vision and Applicationses
dc.publication.volumen27es
dc.publication.issue8es
dc.publication.initialPage1161es
dc.publication.endPage1174es
dc.identifier.sisius21285993es
dc.contributor.funderMinisterio de Economía y Competitividad (MINECO). Españaes

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