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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
11/03/2016 |
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Data da última atualização: |
24/05/2023 |
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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 review on the main challenges in automatic plant disease identification based on visible range images. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Biosystems Engineering, London, v. 144, p. 52-60, Apr. 2016. |
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DOI: |
https://doi.org/10.1016/j.biosystemseng.2016.01.017 |
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Idioma: |
Inglês |
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Conteúdo: |
The problem associated with automatic plant disease identification using visible range images has received considerable attention in the last two decades, however the techniques proposed so far are usually limited in their scope and dependent on ideal capture conditions in order to work properly. This apparent lack of significant advancements may be partially explained by some difficult challenges posed by the subject: presence of complex backgrounds that cannot be easily separated from the region of interest (usually leaf and stem), boundaries of the symptoms often are not well defined, uncontrolled capture conditions may present characteristics that make the image analysis more difficult, certain diseases produce symptoms with a wide range of characteristics, the symptoms produced by different diseases may be very similar, and they may be present simultaneously. This paper provides an analysis of each one of those challenges, emphasizing both the problems that they may cause and how they may have potentially affected the techniques proposed in the past. Some possible solutions capable of overcoming at least some of those challenges are proposed. |
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Palavras-Chave: |
Automatic identification; Imagem digital; Processamento de imagens digitais; Visible symptoms. |
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Thesagro: |
Doença de planta; Sintoma. |
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Thesaurus Nal: |
Digital images; Image analysis; Plant diseases and disorders; Signs and symptoms (plants). |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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001 2040545
005 2023-05-24
008 2016 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.biosystemseng.2016.01.017$2DOI
100 1 $aBARBEDO, J. G. A.
245 $aA review on the main challenges in automatic plant disease identification based on visible range images.$h[electronic resource]
260 $c2016
520 $aThe problem associated with automatic plant disease identification using visible range images has received considerable attention in the last two decades, however the techniques proposed so far are usually limited in their scope and dependent on ideal capture conditions in order to work properly. This apparent lack of significant advancements may be partially explained by some difficult challenges posed by the subject: presence of complex backgrounds that cannot be easily separated from the region of interest (usually leaf and stem), boundaries of the symptoms often are not well defined, uncontrolled capture conditions may present characteristics that make the image analysis more difficult, certain diseases produce symptoms with a wide range of characteristics, the symptoms produced by different diseases may be very similar, and they may be present simultaneously. This paper provides an analysis of each one of those challenges, emphasizing both the problems that they may cause and how they may have potentially affected the techniques proposed in the past. Some possible solutions capable of overcoming at least some of those challenges are proposed.
650 $aDigital images
650 $aImage analysis
650 $aPlant diseases and disorders
650 $aSigns and symptoms (plants)
650 $aDoença de planta
650 $aSintoma
653 $aAutomatic identification
653 $aImagem digital
653 $aProcessamento de imagens digitais
653 $aVisible symptoms
773 $tBiosystems Engineering, London$gv. 144, p. 52-60, Apr. 2016.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
