Plant species identification using multi-scale fractal dimension applied to images of adaxial surface epidermis


Autoria(s): Backes, André R.; De M. Sá Junior, Jarbas J.; Kolb, Rosana M.; Bruno, Odemir M.
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

28/09/2009

Resumo

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.

Formato

680-688

Identificador

http://dx.doi.org/10.1007/978-3-642-03767-2_83

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 5702 LNCS, p. 680-688.

0302-9743

1611-3349

http://hdl.handle.net/11449/71162

10.1007/978-3-642-03767-2_83

2-s2.0-70349309744

Idioma(s)

eng

Relação

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Direitos

closedAccess

Palavras-Chave #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
Tipo

info:eu-repo/semantics/conferencePaper