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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
06/02/2017 |
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Data da última atualização: |
07/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
BARBEDO, J. G. A. |
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Afiliação: |
JAYME GARCIA ARNAL BARBEDO, CNPTIA. |
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Título: |
A new automatic method for disease symptom segmentation in digital photographs of plant leaves. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
European Journal of Plant Pathology, Dordrecht, v. 147, n. 2, p. 349-364, Feb. 2017. |
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DOI: |
10.1007/s10658-016-1007-6 |
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Idioma: |
Inglês |
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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. |
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Palavras-Chave: |
Base de dados de imagem; Image database; Lesion types; Processamento de imagem; Symptom variations; Tipos de lesão. |
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Thesagro: |
Doença de planta; Sintoma. |
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Thesaurus Nal: |
Disease diagnosis; Image analysis; Plant diseases and disorders. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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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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