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

Autores
Silva, Núbia Rosa Da; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; Bruno, Odemir Martinez
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Silva, Núbia Rosa Da. Universidade de Sao Paulo; Brasil
Fil: Florindo, João Batista. Universidade de Sao Paulo; Brasil
Fil: Gómez, María Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina
Fil: Rossatto, Davi Rodrigo. Universidade Estadual Paulista. Faculty of Agriculture and Veterinary Sciences. Department of Applied Biology; Brasil
Fil: Kolb, Rosana Marta. Unesp-universidade Estadual Paulista; . Universidade Estadual Paulista. Faculty of Sciences and Letters. Department of Biological Sciences; Brasil
Fil: Bruno, Odemir Martinez. Universidade de Sao Paulo; Brasil
Materia
Fractal dimension
identification of plants
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/19409
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Plant identification based on leaf midrib cross-section images using fractal descriptorsSilva, Núbia Rosa DaFlorindo, João BatistaGómez, María CeciliaRossatto, Davi RodrigoKolb, Rosana MartaBruno, Odemir MartinezFractal dimensionidentification of plantshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The 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.Fil: Silva, Núbia Rosa Da. Universidade de Sao Paulo; BrasilFil: Florindo, João Batista. Universidade de Sao Paulo; BrasilFil: Gómez, María Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; ArgentinaFil: Rossatto, Davi Rodrigo. Universidade Estadual Paulista. Faculty of Agriculture and Veterinary Sciences. Department of Applied Biology; BrasilFil: Kolb, Rosana Marta. Unesp-universidade Estadual Paulista; . Universidade Estadual Paulista. Faculty of Sciences and Letters. Department of Biological Sciences; BrasilFil: Bruno, Odemir Martinez. Universidade de Sao Paulo; BrasilPublic Library of Science2015-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/19409Silva, Núbia Rosa Da; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; et al.; Plant identification based on leaf midrib cross-section images using fractal descriptors; Public Library of Science; Plos One; 10; 6; 6-2015; 1-14; e01300141932-6203CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0130014info:eu-repo/semantics/altIdentifier/url/http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130014info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:42:57Zoai:ri.conicet.gov.ar:11336/19409instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:42:57.63CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
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, Núbia Rosa Da
Fractal dimension
identification of plants
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
dc.creator.none.fl_str_mv Silva, Núbia Rosa Da
Florindo, João Batista
Gómez, María Cecilia
Rossatto, Davi Rodrigo
Kolb, Rosana Marta
Bruno, Odemir Martinez
author Silva, Núbia Rosa Da
author_facet Silva, Núbia Rosa Da
Florindo, João Batista
Gómez, María Cecilia
Rossatto, Davi Rodrigo
Kolb, Rosana Marta
Bruno, Odemir Martinez
author_role author
author2 Florindo, João Batista
Gómez, María Cecilia
Rossatto, Davi Rodrigo
Kolb, Rosana Marta
Bruno, Odemir Martinez
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Fractal dimension
identification of plants
topic Fractal dimension
identification of plants
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv 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.
Fil: Silva, Núbia Rosa Da. Universidade de Sao Paulo; Brasil
Fil: Florindo, João Batista. Universidade de Sao Paulo; Brasil
Fil: Gómez, María Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina
Fil: Rossatto, Davi Rodrigo. Universidade Estadual Paulista. Faculty of Agriculture and Veterinary Sciences. Department of Applied Biology; Brasil
Fil: Kolb, Rosana Marta. Unesp-universidade Estadual Paulista; . Universidade Estadual Paulista. Faculty of Sciences and Letters. Department of Biological Sciences; Brasil
Fil: Bruno, Odemir Martinez. Universidade de Sao Paulo; Brasil
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 2015-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/19409
Silva, Núbia Rosa Da; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; et al.; Plant identification based on leaf midrib cross-section images using fractal descriptors; Public Library of Science; Plos One; 10; 6; 6-2015; 1-14; e0130014
1932-6203
CONICET Digital
CONICET
url http://hdl.handle.net/11336/19409
identifier_str_mv Silva, Núbia Rosa Da; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; et al.; Plant identification based on leaf midrib cross-section images using fractal descriptors; Public Library of Science; Plos One; 10; 6; 6-2015; 1-14; e0130014
1932-6203
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0130014
info:eu-repo/semantics/altIdentifier/url/http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130014
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.260194

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