Identification of foliar diseases in cotton crop

Detalhes bibliográficos
Autor(a) principal: Bernardes, A. A. [UNESP]
Data de Publicação: 2012
Outros Autores: Rogeri, J. G. [UNESP], Marranghello, N. [UNESP], Pereira, A. S. [UNESP], Araujo, A. F., Tavares, João Manuel R. S.
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/978-94-007-0726-9_4
http://hdl.handle.net/10216/56784
http://hdl.handle.net/11449/73186
Resumo: The pathogens manifestation in plantations are the largest cause of damage in several cultivars, which may cause increase of prices and loss of crop quality. This paper presents a method for automatic classification of cotton diseases through feature extraction of leaf symptoms from digital images. Wavelet transform energy has been used for feature extraction while Support Vector Machine has been used for classification. Five situations have been diagnosed, namely: Healthy crop, Ramularia disease, Bacterial Blight, Ascochyta Blight, and unspecified disease. © 2012 Taylor & Francis Group.
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network_name_str Repositório Institucional da UNESP
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spelling Identification of foliar diseases in cotton cropAscochyta blightAutomatic classificationBacterial blightCrop qualityDigital imageFoliar diseaseCottonDamage detectionFeature extractionImage processingMedical image processingPlants (botany)CropsThe pathogens manifestation in plantations are the largest cause of damage in several cultivars, which may cause increase of prices and loss of crop quality. This paper presents a method for automatic classification of cotton diseases through feature extraction of leaf symptoms from digital images. Wavelet transform energy has been used for feature extraction while Support Vector Machine has been used for classification. Five situations have been diagnosed, namely: Healthy crop, Ramularia disease, Bacterial Blight, Ascochyta Blight, and unspecified disease. © 2012 Taylor & Francis Group.Department of Computer Science and Statistics IBILCE Sao Paulo State University ( UNESP), Sao Jose do Rio Preto-SPDepartment of Mechanical Engineering (DeMec) University of Porto (FEUP) Institute of Mechanical Engineering and Industrial Management (INEGI), PortoDepartment of Computer Science and Statistics IBILCE Sao Paulo State University ( UNESP), Sao Jose do Rio Preto-SPUniversidade Estadual Paulista (Unesp)Institute of Mechanical Engineering and Industrial Management (INEGI)Bernardes, A. A. [UNESP]Rogeri, J. G. [UNESP]Marranghello, N. [UNESP]Pereira, A. S. [UNESP]Araujo, A. F.Tavares, João Manuel R. S.2014-05-27T11:26:23Z2014-05-27T11:26:23Z2012-02-13info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject193-197http://dx.doi.org/10.1007/978-94-007-0726-9_4http://hdl.handle.net/10216/56784Computational Vision and Medical Image Processing, Proceedings of VipIMAGE 2011 - 3rd ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, p. 193-197.http://hdl.handle.net/11449/7318610.1007/978-94-007-0726-9_42-s2.0-84856703865209862326289271996672950765499240000-0003-1086-3312Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengComputational Vision and Medical Image Processing, Proceedings of VipIMAGE 2011 - 3rd ECCOMAS Thematic Conference on Computational Vision and Medical Image Processinginfo:eu-repo/semantics/openAccess2021-10-23T21:37:52Zoai:repositorio.unesp.br:11449/73186Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:37:52Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Identification of foliar diseases in cotton crop
title Identification of foliar diseases in cotton crop
spellingShingle Identification of foliar diseases in cotton crop
Bernardes, A. A. [UNESP]
Ascochyta blight
Automatic classification
Bacterial blight
Crop quality
Digital image
Foliar disease
Cotton
Damage detection
Feature extraction
Image processing
Medical image processing
Plants (botany)
Crops
title_short Identification of foliar diseases in cotton crop
title_full Identification of foliar diseases in cotton crop
title_fullStr Identification of foliar diseases in cotton crop
title_full_unstemmed Identification of foliar diseases in cotton crop
title_sort Identification of foliar diseases in cotton crop
author Bernardes, A. A. [UNESP]
author_facet Bernardes, A. A. [UNESP]
Rogeri, J. G. [UNESP]
Marranghello, N. [UNESP]
Pereira, A. S. [UNESP]
Araujo, A. F.
Tavares, João Manuel R. S.
author_role author
author2 Rogeri, J. G. [UNESP]
Marranghello, N. [UNESP]
Pereira, A. S. [UNESP]
Araujo, A. F.
Tavares, João Manuel R. S.
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Institute of Mechanical Engineering and Industrial Management (INEGI)
dc.contributor.author.fl_str_mv Bernardes, A. A. [UNESP]
Rogeri, J. G. [UNESP]
Marranghello, N. [UNESP]
Pereira, A. S. [UNESP]
Araujo, A. F.
Tavares, João Manuel R. S.
dc.subject.por.fl_str_mv Ascochyta blight
Automatic classification
Bacterial blight
Crop quality
Digital image
Foliar disease
Cotton
Damage detection
Feature extraction
Image processing
Medical image processing
Plants (botany)
Crops
topic Ascochyta blight
Automatic classification
Bacterial blight
Crop quality
Digital image
Foliar disease
Cotton
Damage detection
Feature extraction
Image processing
Medical image processing
Plants (botany)
Crops
description The pathogens manifestation in plantations are the largest cause of damage in several cultivars, which may cause increase of prices and loss of crop quality. This paper presents a method for automatic classification of cotton diseases through feature extraction of leaf symptoms from digital images. Wavelet transform energy has been used for feature extraction while Support Vector Machine has been used for classification. Five situations have been diagnosed, namely: Healthy crop, Ramularia disease, Bacterial Blight, Ascochyta Blight, and unspecified disease. © 2012 Taylor & Francis Group.
publishDate 2012
dc.date.none.fl_str_mv 2012-02-13
2014-05-27T11:26:23Z
2014-05-27T11:26:23Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/978-94-007-0726-9_4
http://hdl.handle.net/10216/56784
Computational Vision and Medical Image Processing, Proceedings of VipIMAGE 2011 - 3rd ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, p. 193-197.
http://hdl.handle.net/11449/73186
10.1007/978-94-007-0726-9_4
2-s2.0-84856703865
2098623262892719
9667295076549924
0000-0003-1086-3312
url http://dx.doi.org/10.1007/978-94-007-0726-9_4
http://hdl.handle.net/10216/56784
http://hdl.handle.net/11449/73186
identifier_str_mv Computational Vision and Medical Image Processing, Proceedings of VipIMAGE 2011 - 3rd ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, p. 193-197.
10.1007/978-94-007-0726-9_4
2-s2.0-84856703865
2098623262892719
9667295076549924
0000-0003-1086-3312
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Computational Vision and Medical Image Processing, Proceedings of VipIMAGE 2011 - 3rd ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 193-197
dc.source.none.fl_str_mv Scopus
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_ 1803649822018764800

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