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dc.contributor.authorCabero-Fayos, Ismael
dc.contributor.authorEpifanio, Irene
dc.date.accessioned2019-07-22T07:20:14Z
dc.date.available2019-07-22T07:20:14Z
dc.date.issued2019-04
dc.identifier.citationCABERO, I.; EPIFANIO, I. Archetypal analysis in texture segmentation. Image Anal. Stereol., 2019, 38: 151-160ca_CA
dc.identifier.urihttp://hdl.handle.net/10234/183307
dc.description.abstractTexture segmentation is one of the main tasks in image applications, specifically in remote sensing, where the objective is to segment high-resolution images of natural landscapes into different cover types. Often the focus is on the selection of discriminant textural features, and although these are really fundamental, there is another part of the process that is also influential, partitioning different homogeneous textures into groups. A methodology based on archetype analysis (AA) of the local textural measurements is proposed. AA seeks the purest textures in the image and it can find the borders between pure textures, as those regions composed of mixtures of several archetypes. The proposed procedure has been tested on a remote sensing image application with local granulometries, providing promising results.ca_CA
dc.format.extent13 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherInternational Society for Stereology & Image Analysisca_CA
dc.rightsAtribución-NoComercial 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectarchetypeca_CA
dc.subjectimage segmentationca_CA
dc.subjectlocal granulometriesca_CA
dc.subjectmathematical morphologyca_CA
dc.subjecttexture analysisca_CA
dc.titleArchetypal analysis: an alternative to clustering for unsupervised texture segmentationca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.5566/ias.2052
dc.relation.projectIDSpanish Ministerio de Ciencia, Innovacion y Universidades (AEI/FEDER, UE) (Grant DPI2017-87333-R) ; Universitat Jaume I (UJIB2017-13)ca_CA
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://www.ias-iss.org/ojs/IAS/article/view/2052ca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA


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