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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: |
17/10/2016 |
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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.; KOENIGKAN, L. V.; SANTOS, T. T. |
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Afiliação: |
JAYME GARCIA ARNAL BARBEDO, CNPTIA; LUCIANO VIEIRA KOENIGKAN, CNPTIA; THIAGO TEIXEIRA SANTOS, CNPTIA. |
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Título: |
Identifying multiple plant diseases using digital image processing. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Biosystems Engineering, London, v. 147, p. 104-116, July 2016. |
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DOI: |
http://dx.doi.org/10.1016/j.biosystemseng.2016.03.012 |
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Idioma: |
Inglês |
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Conteúdo: |
The gap between the current capabilities of image-based methods for automatic plant disease identification and the real-world needs is still wide. Although advances have been made on the subject, most methods are still not robust enough to deal with a wide variety of diseases and plant species. This paper proposes a method for disease identification, based on colour transformations, colour histograms and a pairwise-based classification system. Its performance was tested using a large database containing images of symptoms belonging to 82 different biotic and abiotic stresses, affecting the leaves of 12 different plant species. The wide variety of images used in the tests made it possible to carry out an in-depth investigation about the main advantages and limitations of the proposed algorithm. A comparison with other algorithms is also presented, and some possible solutions for the main challenges that still prevent this kind of tool to be adopted in practice. |
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Palavras-Chave: |
Automatic disease recognition; Colour transformations; Identificação automática de doença de planta; Visible symptoms. |
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Thesagro: |
Doença de planta. |
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Thesaurus Nal: |
Image analysis; Plant diseases and disorders. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 01785naa a2200241 a 4500
001 2054758
005 2020-01-07
008 2016 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1016/j.biosystemseng.2016.03.012$2DOI
100 1 $aBARBEDO, J. G. A.
245 $aIdentifying multiple plant diseases using digital image processing.$h[electronic resource]
260 $c2016
520 $aThe gap between the current capabilities of image-based methods for automatic plant disease identification and the real-world needs is still wide. Although advances have been made on the subject, most methods are still not robust enough to deal with a wide variety of diseases and plant species. This paper proposes a method for disease identification, based on colour transformations, colour histograms and a pairwise-based classification system. Its performance was tested using a large database containing images of symptoms belonging to 82 different biotic and abiotic stresses, affecting the leaves of 12 different plant species. The wide variety of images used in the tests made it possible to carry out an in-depth investigation about the main advantages and limitations of the proposed algorithm. A comparison with other algorithms is also presented, and some possible solutions for the main challenges that still prevent this kind of tool to be adopted in practice.
650 $aImage analysis
650 $aPlant diseases and disorders
650 $aDoença de planta
653 $aAutomatic disease recognition
653 $aColour transformations
653 $aIdentificação automática de doença de planta
653 $aVisible symptoms
700 1 $aKOENIGKAN, L. V.
700 1 $aSANTOS, T. T.
773 $tBiosystems Engineering, London$gv. 147, p. 104-116, July 2016.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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| Registros recuperados : 69 | |
| 22. |  | MORETO, P.; KOENIGKAN, L. V.; SANTOS, T. T. Estudos para um controlador de código-aberto em imageador de custo acessível para fenotipagem de plantas. In: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 12., 2019, Indaiatuba. Anais... Ponta Grossa: SBIAGRO, 2019. p. 533-534. Organizadores: Maria Fernanda Moura, Jayme Garcia Arnal Barbedo, Alaine Margarete Guimarães, Valter Castelhano de Oliveira. SBIAgro 2019.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
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| 29. | | CRUVINEL, P. E.; KOENIGKAN, L. V.; PEREIRA, M. F. L. Visualizing thermal information and knowledge creation in grain storage bin based on threedimensional (3d) interface model and computer graphic techniques. In: INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING - ICSC, 10., 2016, Laguna Hills, California, USA. Proceedings... Los Alamitos, California, EUA: IEEE, 2016. p. 425-428.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Instrumentação. |
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| 31. | | SANTOS, T. T.; KOENIGKAN, L. V.; BARBEDO, J. G. A.; RODRIGUES, G. C. 3D plant modeling: localization, mapping and segmentation for plant phenotyping using a single hand-held camera. In: EUROPEAN CONFERENCE ON COMPUTER VISION, 13., 2014, Zurich. Computer Vision: ECCV 2014: proceedings. Switzerland: Springer, 2015. p. 247-263. (Lecture notes in computer science, v. 8928). Part IV. Editores: Lourdes Agapito, Michael M. Bronstein, Carsten Rother.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
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| 39. | | BRESSAN, G. M.; KOENIGKAN, L. V.; OLIVEIRA, V. A.; CRUVINEL, P. E.; KARAM, D. A classification methodology for the risk of weed infestation using fuzzy logic. Weed Research, Oxford, v. 48, n. 5, p. 470-479, 2008.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: Internacional - A |
| Biblioteca(s): Embrapa Milho e Sorgo. |
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| Registros recuperados : 69 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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