dc.contributorUniversidade de São Paulo (USP)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:23:59Z
dc.date.available2014-05-27T11:23:59Z
dc.date.created2014-05-27T11:23:59Z
dc.date.issued2009-09-28
dc.identifierLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 5702 LNCS, p. 680-688.
dc.identifier0302-9743
dc.identifier1611-3349
dc.identifierhttp://hdl.handle.net/11449/71162
dc.identifier10.1007/978-3-642-03767-2_83
dc.identifier2-s2.0-70349309744
dc.identifier0000-0003-3841-5597
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.
dc.languageeng
dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation0,295
dc.rightsAcesso aberto
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 epidermis
dc.typeActas de congresos


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