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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. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
12/11/2014 |
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Data da última atualização: |
08/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
BARBEDO, J. G. A. |
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Afiliação: |
JAYME GARCIA ARNAL BARBEDO, CNPTIA. |
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Título: |
An automatic method to detect and measure leaf disease symptoms using digital image processing. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Plant Disease, Saint Paul, v. 98, n. 12, 1709-1716, Dec. 2014. |
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DOI: |
http://dx.doi.org/10.10 94/PDIS-03-14-0290-RE |
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Idioma: |
Inglês |
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Conteúdo: |
A method is presented to detect and quantify leaf symptoms using conventional color digital images. The method was designed to be completely automatic, eliminating the possibility of human error and reducing time taken to measure disease severity. The program is capable of dealing with images containing multiple leaves, further reducing the time taken. Accurate results are possible when the symptoms and leaf veins have similar color and shade characteristics. The algorithm is subject to one constraint: the background must be as close to white or black as possible. Tests showed that the method provided accurate estimates over a wide variety of conditions, being robust to variation in size, shape, and color of leaves; symptoms; and leaf veins. Low rates of false positives and false negatives occurred due to extrinsic factors such as issues with image capture and the use of extreme file compression ratios. |
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Palavras-Chave: |
Imagem digital; Processamento de imagens. |
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Thesagro: |
Doença de planta. |
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Thesaurus NAL: |
Digital images; Image analysis; Plant diseases and disorders. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 01604naa a2200205 a 4500
001 1999820
005 2020-01-08
008 2014 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.10 94/PDIS-03-14-0290-RE$2DOI
100 1 $aBARBEDO, J. G. A.
245 $aAn automatic method to detect and measure leaf disease symptoms using digital image processing.$h[electronic resource]
260 $c2014
520 $aA method is presented to detect and quantify leaf symptoms using conventional color digital images. The method was designed to be completely automatic, eliminating the possibility of human error and reducing time taken to measure disease severity. The program is capable of dealing with images containing multiple leaves, further reducing the time taken. Accurate results are possible when the symptoms and leaf veins have similar color and shade characteristics. The algorithm is subject to one constraint: the background must be as close to white or black as possible. Tests showed that the method provided accurate estimates over a wide variety of conditions, being robust to variation in size, shape, and color of leaves; symptoms; and leaf veins. Low rates of false positives and false negatives occurred due to extrinsic factors such as issues with image capture and the use of extreme file compression ratios.
650 $aDigital images
650 $aImage analysis
650 $aPlant diseases and disorders
650 $aDoença de planta
653 $aImagem digital
653 $aProcessamento de imagens
773 $tPlant Disease, Saint Paul$gv. 98, n. 12, 1709-1716, Dec. 2014.
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Embrapa Agricultura Digital (CNPTIA) |
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