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Registro Completo |
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
06/02/2017 |
Data da última atualização: |
07/01/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
BARBEDO, J. G. A. |
Afiliação: |
JAYME GARCIA ARNAL BARBEDO, CNPTIA. |
Título: |
A new automatic method for disease symptom segmentation in digital photographs of plant leaves. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
European Journal of Plant Pathology, Dordrecht, v. 147, n. 2, p. 349-364, Feb. 2017. |
DOI: |
10.1007/s10658-016-1007-6 |
Idioma: |
Inglês |
Conteúdo: |
Abstract. The segmentation of symptoms during image analysis of diseased plant leaves is an essential process for detection and classification of diseases. However, there are challenges involved in the task, many of them related to the variability of image and host/symptom characteristics and conditions. As a result of those challenges, the methods proposed in the literature so far focus on a specific problem and are usually bounded by tight constraints regarding image capture conditions. This research explores a new automatic method for segmenting disease symptoms on plant leaves that was designed to be applicable in a wide range of situations. The proposed technique employs only color channel manipulations and Boolean operations applied on binary masks, thus being simpler and more robust compared to many previously described automatic methods. Its effectiveness is demonstrated by tests performed over a large database containing images of 77 different diseases of 11 plant species. A comparison with manual segmentation is also presented, further reinforcing the advantages of the proposed approach. |
Palavras-Chave: |
Base de dados de imagem; Image database; Lesion types; Processamento de imagem; Symptom variations; Tipos de lesão. |
Thesagro: |
Doença de planta; Sintoma. |
Thesaurus Nal: |
Disease diagnosis; Image analysis; Plant diseases and disorders. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 01966naa a2200265 a 4500 001 2062753 005 2020-01-07 008 2017 bl uuuu u00u1 u #d 024 7 $a10.1007/s10658-016-1007-6$2DOI 100 1 $aBARBEDO, J. G. A. 245 $aA new automatic method for disease symptom segmentation in digital photographs of plant leaves.$h[electronic resource] 260 $c2017 520 $aAbstract. The segmentation of symptoms during image analysis of diseased plant leaves is an essential process for detection and classification of diseases. However, there are challenges involved in the task, many of them related to the variability of image and host/symptom characteristics and conditions. As a result of those challenges, the methods proposed in the literature so far focus on a specific problem and are usually bounded by tight constraints regarding image capture conditions. This research explores a new automatic method for segmenting disease symptoms on plant leaves that was designed to be applicable in a wide range of situations. The proposed technique employs only color channel manipulations and Boolean operations applied on binary masks, thus being simpler and more robust compared to many previously described automatic methods. Its effectiveness is demonstrated by tests performed over a large database containing images of 77 different diseases of 11 plant species. A comparison with manual segmentation is also presented, further reinforcing the advantages of the proposed approach. 650 $aDisease diagnosis 650 $aImage analysis 650 $aPlant diseases and disorders 650 $aDoença de planta 650 $aSintoma 653 $aBase de dados de imagem 653 $aImage database 653 $aLesion types 653 $aProcessamento de imagem 653 $aSymptom variations 653 $aTipos de lesão 773 $tEuropean Journal of Plant Pathology, Dordrecht$gv. 147, n. 2, p. 349-364, Feb. 2017.
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Embrapa Agricultura Digital (CNPTIA) |
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Biblioteca(s): |
Embrapa Meio-Norte. |
Data corrente: |
18/07/2013 |
Data da última atualização: |
18/07/2013 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
MENDES, R. F. de M.; ARAUJO NETO, R. B. de; NASCIMENT0, M. do S. B. C. do; LIMA, P. S. da C. |
Afiliação: |
RAUL FERREIRA DE MIRANDA MENDES, UFPI; RAIMUNDO BEZERRA DE ARAUJO NETO, CPAMN; MARIA DO SOCORRO BONA CORTEZ DO NASCIMENT0, CPAMN; PAULO SARMANHO DA COSTA LIMA, CPAMN. |
Título: |
Caracterização molecular de forrageiras do gênero Poincianella. |
Ano de publicação: |
2013 |
Fonte/Imprenta: |
In: WORKSHOP SOBRE TOLERÂNCIA ESTRESSES ABIÓTICOS, 1., 2013, Campo Grande, MS. Anais... Campo Grande, MS: Embrapa Gado de Corte, 2013. |
Páginas: |
p. 94-103. |
Série: |
(Embrapa Gado de Corte. Documentos, 199). |
Idioma: |
Português |
Palavras-Chave: |
Forrageira. |
Thesagro: |
Recurso Genético. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/86213/1/WorkhopDoc20001.pdf
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Marc: |
LEADER 00657nam a2200181 a 4500 001 1962390 005 2013-07-18 008 2013 bl uuuu u00u1 u #d 100 1 $aMENDES, R. F. de M. 245 $aCaracterização molecular de forrageiras do gênero Poincianella. 260 $aIn: WORKSHOP SOBRE TOLERÂNCIA ESTRESSES ABIÓTICOS, 1., 2013, Campo Grande, MS. Anais... Campo Grande, MS: Embrapa Gado de Corte$c2013 300 $ap. 94-103. 490 $a(Embrapa Gado de Corte. Documentos, 199). 650 $aRecurso Genético 653 $aForrageira 700 1 $aARAUJO NETO, R. B. de 700 1 $aNASCIMENT0, M. do S. B. C. do 700 1 $aLIMA, P. S. da C.
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