dc.creatorFlorindo
dc.creatorJoao B.; Landini
dc.creatorGabriel; Bruno
dc.creatorOdemir M.
dc.date2016
dc.datedez
dc.date2017-11-13T13:54:51Z
dc.date2017-11-13T13:54:51Z
dc.date.accessioned2018-03-29T06:08:20Z
dc.date.available2018-03-29T06:08:20Z
dc.identifierPattern Recognition Letters. Elsevier Science Bv, v. 84, p. 239 - 244, 2016.
dc.identifier0167-8655
dc.identifier1872-7344
dc.identifierWOS:000390660900034
dc.identifier10.1016/j.patrec.2016.09.013
dc.identifierhttp://www-sciencedirect-com.ez88.periodicos.capes.gov.br/science/article/pii/S016786551630246X?via%3Dihub
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/329518
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1366543
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionThis work proposes a new method of texture analysis for grey-level images based on the distribution of connectivity indexes in local neighbourhoods. The connectivity index acts as a measure of homogeneity of textures and its distribution is computed at various local neighbourhood sizes. The resulting descriptors provide an efficient multiscale representation of connectivity at different scales. The method was tested in the classification of UIUC, Outex, and KTH-TIPS2b databases and outperformed several state-of-the-art approaches, including such as LBP, LBP+VAR, MR8, multifractals among others. (C) 2016 The Authors. Published by Elsevier B.V.
dc.description84
dc.description239
dc.description244
dc.descriptionFAPESP (The State of Sao Paulo Research Foundation) [2012/19143-3, 2013/22205-3]
dc.descriptionEngineering and Physical Sciences Research Council (EPSRC), UK through Novel context-based segmentation algorithms for intelligent microscopy [EP/M023869/1]
dc.descriptionCNPq (National Council for Scientific and Technological Development, Brazil) [307797/2014-7, 484312/2013-8]
dc.descriptionFAPESP [11/01523-1]
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.languageEnglish
dc.publisherElsevier Science BV
dc.publisherAmsterdam
dc.relationPattern Recognition Letters
dc.rightsfechado
dc.sourceWOS
dc.subjectLocal Connectivity
dc.subjectTexture Analysis
dc.subjectPattern Recognition
dc.subjectImage Classification
dc.titleThree-dimensional Connectivity Index For Texture Recognition
dc.typeArtículos de revistas


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