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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/71162
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dc.contributor.authorBackes, André R.-
dc.contributor.authorDe M. Sá Junior, Jarbas J.-
dc.contributor.authorKolb, Rosana M.-
dc.contributor.authorBruno, Odemir M.-
dc.date.accessioned2014-05-27T11:23:59Z-
dc.date.accessioned2016-10-25T18:27:26Z-
dc.date.available2014-05-27T11:23:59Z-
dc.date.available2016-10-25T18:27:26Z-
dc.date.issued2009-09-28-
dc.identifierhttp://dx.doi.org/10.1007/978-3-642-03767-2_83-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 5702 LNCS, p. 680-688.-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttp://hdl.handle.net/11449/71162-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/71162-
dc.description.abstractThis paper presents the study of computational methods applied to histological texture analysis in order to identify plant species, a very difficult task due to the great similarity among some species and presence of irregularities in a given species. Experiments were performed considering 300 ×300 texture windows extracted from adaxial surface epidermis from eight species. Different texture methods were evaluated using Linear Discriminant Analysis (LDA). Results showed that methods based on complexity analysis perform a better texture discrimination, so conducting to a more accurate identification of plant species. © 2009 Springer Berlin Heidelberg.en
dc.format.extent680-688-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectComplexity-
dc.subjectMulti-scale fractal dimension-
dc.subjectPlant identification-
dc.subjectTexture analysis-
dc.subjectComplexity analysis-
dc.subjectLinear discriminant analysis-
dc.subjectMultiscales-
dc.subjectPlant species-
dc.subjectPlant species identification-
dc.subjectTexture discrimination-
dc.subjectTexture window-
dc.subjectComputational methods-
dc.subjectDiscriminant analysis-
dc.subjectImage analysis-
dc.subjectPartial discharges-
dc.subjectTextures-
dc.subjectFractal dimension-
dc.titlePlant species identification using multi-scale fractal dimension applied to images of adaxial surface epidermisen
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationInstituto de Ciências Matemáticas e de Computaçã o (ICMC) Universidade de São Paulo (USP)-
dc.description.affiliationDepartamento de Ciências Biológicas Universidade Estadual Paulista Júlio de Mesquita Filho-
dc.description.affiliationInstituto de Física de São Carlos (IFSC) Universidade de São Paulo (USP)-
dc.description.affiliationUnespDepartamento de Ciências Biológicas Universidade Estadual Paulista Júlio de Mesquita Filho-
dc.identifier.doi10.1007/978-3-642-03767-2_83-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.identifier.scopus2-s2.0-70349309744-
dc.identifier.orcid0000-0003-3841-5597pt
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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