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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/68101
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dc.contributor.authorde Carvalho Kokubum, Christiane Nogueira-
dc.contributor.authorTommaselli, Antonio Maria Garcia-
dc.contributor.authorReiss, Mário Luiz Lopes-
dc.date.accessioned2014-05-27T11:21:15Z-
dc.date.accessioned2016-10-25T18:20:23Z-
dc.date.available2014-05-27T11:21:15Z-
dc.date.available2016-10-25T18:20:23Z-
dc.date.issued2005-01-01-
dc.identifierhttp://ojs.c3sl.ufpr.br/ojs/index.php/bcg/article/view/1547-
dc.identifier.citationBoletim de Ciencias Geodesicas, v. 11, n. 1, p. 89-116, 2005.-
dc.identifier.issn1413-4853-
dc.identifier.urihttp://hdl.handle.net/11449/68101-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/68101-
dc.description.abstractOne of the main problems in Computer Vision and Close Range Digital Photogrammetry is 3D reconstruction. 3D reconstruction with structured light is one of the existing techniques and which still has several problems, one of them the identification or classification of the projected targets. Approaching this problem is the goal of this paper. An area based method called template matching was used for target classification. This method performs detection of area similarity by correlation, which measures the similarity between the reference and search windows, using a suitable correlation function. In this paper the modified cross covariance function was used, which presented the best results. A strategy was developed for adaptative resampling of the patterns, which solved the problem of deformation of the targets due to object surface inclination. Experiments with simulated and real data were performed in order to assess the efficiency of the proposed methodology for target detection. The results showed that the proposed classification strategy works properly, identifying 98% of targets in plane surfaces and 93% in oblique surfaces.en
dc.format.extent89-116-
dc.language.isopor-
dc.sourceScopus-
dc.subjectcomputer vision-
dc.subjectdigital photogrammetry-
dc.subjectimage classification-
dc.titleClassificação automática de padrões projetados por um sistema de luz estruturadapt
dc.title.alternativeAutomatic classification of targets projected with a structured light systemen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationUniversidade Estadual Paulista Faculdade de Ciências e Tecnologia Departamento de Cartografia, Rua Roberto Simonsen, 305, 19060-900 Presidente Prudente-
dc.description.affiliationUnespUniversidade Estadual Paulista Faculdade de Ciências e Tecnologia Departamento de Cartografia, Rua Roberto Simonsen, 305, 19060-900 Presidente Prudente-
dc.rights.accessRightsAcesso aberto-
dc.identifier.file2-s2.0-27344456188.pdf-
dc.relation.ispartofBoletim de Ciências Geodésicas-
dc.identifier.scopus2-s2.0-27344456188-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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