Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements

This paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparati...

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Autor Principal: Fernández, Roemi (author)
Outros autores: Montes Franceschi, Héctor (author), Salinas, Carlota (author), Sarria, Javier (author), Armada, Manuel (author)
Formato: article
Idioma:inglés
Publicado: 2013
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Acceso en liña:http://www.mdpi.com/1424-8220/13/6/7838
http://ridda2.utp.ac.pa/handle/123456789/2363
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author Fernández, Roemi
author2 Montes Franceschi, Héctor
Salinas, Carlota
Sarria, Javier
Armada, Manuel
author2_role author
author
author
author
author_browse Armada, Manuel
Fernández, Roemi
Montes Franceschi, Héctor
Salinas, Carlota
Sarria, Javier
author_facet Fernández, Roemi
Montes Franceschi, Héctor
Salinas, Carlota
Sarria, Javier
Armada, Manuel
author_role author
collection Repositorio Institucional de documento digitales de acceso abierto de la UTP
dc.creator.none.fl_str_mv Fernández, Roemi
Montes Franceschi, Héctor
Salinas, Carlota
Sarria, Javier
Armada, Manuel
dc.date.none.fl_str_mv 2013-06-19
2013-06-19
2017-07-31T16:00:04Z
2017-07-31T16:00:04Z
2017-07-31T16:00:04Z
2017-07-31T16:00:04Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://www.mdpi.com/1424-8220/13/6/7838
http://ridda2.utp.ac.pa/handle/123456789/2363
http://ridda2.utp.ac.pa/handle/123456789/2363
dc.language.none.fl_str_mv eng
eng
dc.rights.none.fl_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTP
instname:Universidad Tecnológica de Panamá
instacron:U Tecnológica de Panamá
dc.subject.none.fl_str_mv multispectral imagery
precision viticulture
Cabernet Sauvignon
optical filters
image processing
classification
K-means
multispectral imagery
precision viticulture
Cabernet Sauvignon
optical filters
image processing
classification
K-means
dc.title.none.fl_str_mv Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
description This paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparation of the vineyard. In this way, image pixels are classified into five clusters corresponding to leaves, stems, branches, fruit and background. A custom-made sensory rig that integrates a CCD camera and a servo-controlled filter wheel has been specially designed and manufactured for the acquisition of images during the experimental stage. The proposed algorithm is extremely simple, efficient, and provides a satisfactory rate of classification success. All these features turn out the proposed algorithm into an appropriate candidate to be employed in numerous tasks of the precision viticulture, such as yield estimation, water and nutrients needs estimation, spraying and harvesting.
eu_rights_str_mv openAccess
format article
id lrtest_e099ac3ba08f7c2012642b414c233dbc
instacron_str U Tecnológica de Panamá
institution U Tecnológica de Panamá
instname_str Universidad Tecnológica de Panamá
language eng
network_acronym_str lrtest
network_name_str lr
oai_identifier_str oai:ridda2.utp.ac.pa:123456789/2363
publishDate 2013
publishDateSort 2013
reponame_str Repositorio Institucional de documento digitales de acceso abierto de la UTP
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
spelling Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine ElementsFernández, RoemiMontes Franceschi, HéctorSalinas, CarlotaSarria, JavierArmada, Manuelmultispectral imageryprecision viticultureCabernet Sauvignonoptical filtersimage processingclassificationK-meansmultispectral imageryprecision viticultureCabernet Sauvignonoptical filtersimage processingclassificationK-meansThis paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparation of the vineyard. In this way, image pixels are classified into five clusters corresponding to leaves, stems, branches, fruit and background. A custom-made sensory rig that integrates a CCD camera and a servo-controlled filter wheel has been specially designed and manufactured for the acquisition of images during the experimental stage. The proposed algorithm is extremely simple, efficient, and provides a satisfactory rate of classification success. All these features turn out the proposed algorithm into an appropriate candidate to be employed in numerous tasks of the precision viticulture, such as yield estimation, water and nutrients needs estimation, spraying and harvesting.This paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparation of the vineyard. In this way, image pixels are classified into five clusters corresponding to leaves, stems, branches, fruit and background. A custom-made sensory rig that integrates a CCD camera and a servo-controlled filter wheel has been specially designed and manufactured for the acquisition of images during the experimental stage. The proposed algorithm is extremely simple, efficient, and provides a satisfactory rate of classification success. All these features turn out the proposed algorithm into an appropriate candidate to be employed in numerous tasks of the precision viticulture, such as yield estimation, water and nutrients needs estimation, spraying and harvesting.2017-07-31T16:00:04Z2017-07-31T16:00:04Z2017-07-31T16:00:04Z2017-07-31T16:00:04Z2013-06-192013-06-19info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.mdpi.com/1424-8220/13/6/7838http://ridda2.utp.ac.pa/handle/123456789/2363http://ridda2.utp.ac.pa/handle/123456789/2363engenghttps://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccessreponame:Repositorio Institucional de documento digitales de acceso abierto de la UTPinstname:Universidad Tecnológica de Panamáinstacron:U Tecnológica de Panamáoai:ridda2.utp.ac.pa:123456789/23632021-07-06T15:34:49Z
spellingShingle Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements
Fernández, Roemi
multispectral imagery
precision viticulture
Cabernet Sauvignon
optical filters
image processing
classification
K-means
multispectral imagery
precision viticulture
Cabernet Sauvignon
optical filters
image processing
classification
K-means
status_str publishedVersion
title Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements
title_full Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements
title_fullStr Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements
title_full_unstemmed Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements
title_short Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements
title_sort Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements
topic multispectral imagery
precision viticulture
Cabernet Sauvignon
optical filters
image processing
classification
K-means
multispectral imagery
precision viticulture
Cabernet Sauvignon
optical filters
image processing
classification
K-means
url http://www.mdpi.com/1424-8220/13/6/7838
http://ridda2.utp.ac.pa/handle/123456789/2363