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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sul. Para informações adicionais entre em contato com cppsul.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Pecuária Sul. |
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Data corrente: |
06/09/2017 |
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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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Circulação/Nível: |
A - 2 |
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Autoria: |
BARBEDO, J. G. A.; GULIAS GOMES, C. C.; CARDOSO, F. F.; DOMINGUES, R.; RAMOS, J. V.; MCMANUS, C. M. |
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Afiliação: |
JAYME GARCIA ARNAL BARBEDO, CNPTIA; CLAUDIA CRISTINA GULIAS GOMES, CPPSUL; FERNANDO FLORES CARDOSO, CPPSUL; ROBERT DOMINGUES, CPPSUL; JEFERSON VIDART RAMOS; CONCEPTA MARGARET MCMANUS, UnB. |
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Título: |
The use of infrared images to detect ticks in cattle and proposal of an algorithm for quantifying the infestation. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Veterinary Parasitology, v. 235, p. 106-112, Feb. 2017. |
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DOI: |
10.1016/j.vetpar.2017.01.020 |
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Idioma: |
Inglês |
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Conteúdo: |
This paper presents a study on the use of low resolution infrared images to detect ticks in cattle. Emphasis is given to the main factors that influence the quality of the captured images, as well as to the actions that can increase the amount of information conveyed by these images. In addition, a new automatic method for analyzing the images and counting the ticks is introduced. The proposed algorithm relies only on color transformations and simple mathematical morphology operations, thus being easy to implement and computationally light. Tests were carried out using a large database containing images of the neck and hind end of the animals. It was observed that the proposed algorithm is very effective in detecting ticks visible in the images, even if the contrast with the background is not high. On the other hand, due to both intrinsic and extrinsic factors, the thermographic images used in this study did not always succeed in creating enough contrast between ticks and cattle's hair coat. Although these problems can be mitigated by following some directives, currently only rough estimates for tick counts can be achieved using infrared images with low spatial resolution. |
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Palavras-Chave: |
Algoritmo; Automatic count contrast; Imagem infravermelha; Infrared thermography; Morfologia matemática. |
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Thesagro: |
Boophilus microplus; Bovino; Carrapato; Infestação. |
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Thesaurus NAL: |
Algorithms; Digital Images. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02171naa a2200325 a 4500
001 2075142
005 2020-01-07
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1016/j.vetpar.2017.01.020$2DOI
100 1 $aBARBEDO, J. G. A.
245 $aThe use of infrared images to detect ticks in cattle and proposal of an algorithm for quantifying the infestation.$h[electronic resource]
260 $c2017
520 $aThis paper presents a study on the use of low resolution infrared images to detect ticks in cattle. Emphasis is given to the main factors that influence the quality of the captured images, as well as to the actions that can increase the amount of information conveyed by these images. In addition, a new automatic method for analyzing the images and counting the ticks is introduced. The proposed algorithm relies only on color transformations and simple mathematical morphology operations, thus being easy to implement and computationally light. Tests were carried out using a large database containing images of the neck and hind end of the animals. It was observed that the proposed algorithm is very effective in detecting ticks visible in the images, even if the contrast with the background is not high. On the other hand, due to both intrinsic and extrinsic factors, the thermographic images used in this study did not always succeed in creating enough contrast between ticks and cattle's hair coat. Although these problems can be mitigated by following some directives, currently only rough estimates for tick counts can be achieved using infrared images with low spatial resolution.
650 $aAlgorithms
650 $aDigital Images
650 $aBoophilus microplus
650 $aBovino
650 $aCarrapato
650 $aInfestação
653 $aAlgoritmo
653 $aAutomatic count contrast
653 $aImagem infravermelha
653 $aInfrared thermography
653 $aMorfologia matemática
700 1 $aGULIAS GOMES, C. C.
700 1 $aCARDOSO, F. F.
700 1 $aDOMINGUES, R.
700 1 $aRAMOS, J. V.
700 1 $aMCMANUS, C. M.
773 $tVeterinary Parasitology$gv. 235, p. 106-112, Feb. 2017.
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Embrapa Agricultura Digital (CNPTIA) |
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