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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/71162
Title: 
Plant species identification using multi-scale fractal dimension applied to images of adaxial surface epidermis
Author(s): 
Institution: 
  • Universidade de São Paulo (USP)
  • Universidade Estadual Paulista (UNESP)
ISSN: 
  • 0302-9743
  • 1611-3349
Abstract: 
This 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.
Issue Date: 
28-Sep-2009
Citation: 
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 5702 LNCS, p. 680-688.
Time Duration: 
680-688
Keywords: 
  • Complexity
  • Multi-scale fractal dimension
  • Plant identification
  • Texture analysis
  • Complexity analysis
  • Linear discriminant analysis
  • Multiscales
  • Plant species
  • Plant species identification
  • Texture discrimination
  • Texture window
  • Computational methods
  • Discriminant analysis
  • Image analysis
  • Partial discharges
  • Textures
  • Fractal dimension
Source: 
http://dx.doi.org/10.1007/978-3-642-03767-2_83
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/71162
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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