Plant identification based on leaf midrib cross-section images using fractal descriptors

Detalhes bibliográficos
Autor(a) principal: Silva, Nubia Rosa da
Data de Publicação: 2015
Outros Autores: Florindo, Joao Batista, Gomez, Maria Cecilia, Rossatto, Davi Rodrigo [UNESP], Kolb, Rosana Marta [UNESP], Bruno, Odemir Martinez
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130014
http://hdl.handle.net/11449/129493
Resumo: The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.
id UNSP_e08f048b7e891e05827e21f8292aa42f
oai_identifier_str oai:repositorio.unesp.br:11449/129493
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Plant identification based on leaf midrib cross-section images using fractal descriptorsThe correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ Sao Paulo, Sao Carlos Inst Phys, BR-13560970 Sao Carlos, SP, BrazilUniv Sao Paulo, Inst Math &Comp Sci, BR-13560970 Sao Carlos, SP, BrazilNatl Univ Littoral, Fac Biochem &Biol Sci, Dept Phys, Santa Fe, ArgentinaUniv Estadual Paulista, UNESP, Fac Agr &Vet Sci, Dept Appl Biol, Jaboticabal, SP, BrazilUniv Estadual Paulista, UNESP, Fac Sci &Letters, Dept Biol Sci, Assis, SP, BrazilUniv Estadual Paulista, UNESP, Fac Agr &Vet Sci, Dept Appl Biol, Jaboticabal, SP, BrazilUniv Estadual Paulista, UNESP, Fac Sci &Letters, Dept Biol Sci, Assis, SP, BrazilFAPESP: 2011/21467-9FAPESP: 2012/19143-3FAPESP: 2011/23112-3FAPESP: 2011/01523-1CNPq: 307797/2014-7CNPq: 484312/2013-8Public Library ScienceUniversidade de São Paulo (USP)Natl Univ LittoralUniversidade Estadual Paulista (Unesp)Silva, Nubia Rosa daFlorindo, Joao BatistaGomez, Maria CeciliaRossatto, Davi Rodrigo [UNESP]Kolb, Rosana Marta [UNESP]Bruno, Odemir Martinez2015-10-21T21:12:53Z2015-10-21T21:12:53Z2015-06-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1-14application/pdfhttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130014Plos One. San Francisco: Public Library Science, v. 10, n. 6, p. 1-14, 2015.1932-6203http://hdl.handle.net/11449/12949310.1371/journal.pone.0130014WOS:000356835000083WOS000356835000083.pdf05886661725016650000-0003-3841-5597Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPlos One2.7661,164info:eu-repo/semantics/openAccess2024-06-13T17:37:58Zoai:repositorio.unesp.br:11449/129493Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:53:11.264907Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Plant identification based on leaf midrib cross-section images using fractal descriptors
title Plant identification based on leaf midrib cross-section images using fractal descriptors
spellingShingle Plant identification based on leaf midrib cross-section images using fractal descriptors
Silva, Nubia Rosa da
title_short Plant identification based on leaf midrib cross-section images using fractal descriptors
title_full Plant identification based on leaf midrib cross-section images using fractal descriptors
title_fullStr Plant identification based on leaf midrib cross-section images using fractal descriptors
title_full_unstemmed Plant identification based on leaf midrib cross-section images using fractal descriptors
title_sort Plant identification based on leaf midrib cross-section images using fractal descriptors
author Silva, Nubia Rosa da
author_facet Silva, Nubia Rosa da
Florindo, Joao Batista
Gomez, Maria Cecilia
Rossatto, Davi Rodrigo [UNESP]
Kolb, Rosana Marta [UNESP]
Bruno, Odemir Martinez
author_role author
author2 Florindo, Joao Batista
Gomez, Maria Cecilia
Rossatto, Davi Rodrigo [UNESP]
Kolb, Rosana Marta [UNESP]
Bruno, Odemir Martinez
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Natl Univ Littoral
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Silva, Nubia Rosa da
Florindo, Joao Batista
Gomez, Maria Cecilia
Rossatto, Davi Rodrigo [UNESP]
Kolb, Rosana Marta [UNESP]
Bruno, Odemir Martinez
description The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.
publishDate 2015
dc.date.none.fl_str_mv 2015-10-21T21:12:53Z
2015-10-21T21:12:53Z
2015-06-19
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130014
Plos One. San Francisco: Public Library Science, v. 10, n. 6, p. 1-14, 2015.
1932-6203
http://hdl.handle.net/11449/129493
10.1371/journal.pone.0130014
WOS:000356835000083
WOS000356835000083.pdf
0588666172501665
0000-0003-3841-5597
url http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130014
http://hdl.handle.net/11449/129493
identifier_str_mv Plos One. San Francisco: Public Library Science, v. 10, n. 6, p. 1-14, 2015.
1932-6203
10.1371/journal.pone.0130014
WOS:000356835000083
WOS000356835000083.pdf
0588666172501665
0000-0003-3841-5597
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Plos One
2.766
1,164
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1-14
application/pdf
dc.publisher.none.fl_str_mv Public Library Science
publisher.none.fl_str_mv Public Library Science
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808128287099060224