Backes, André R.De M. Sá Junior, Jarbas J.Kolb, Rosana M.Bruno, Odemir M. [UNESP]2014-05-272014-05-272009-09-28Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 5702 LNCS, p. 680-688.0302-97431611-3349http://hdl.handle.net/11449/71162This 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.680-688engComplexityMulti-scale fractal dimensionPlant identificationTexture analysisComplexity analysisLinear discriminant analysisMultiscalesPlant speciesPlant species identificationTexture discriminationTexture windowComputational methodsDiscriminant analysisImage analysisPartial dischargesTexturesFractal dimensionTrabalho apresentado em evento10.1007/978-3-642-03767-2_83Acesso aberto2-s2.0-703493097440000-0003-3841-5597