Volume estimation of unbroken soybeans samples using digital image processing techniques

Autores
Villaverde, Jorge; Cleva, Mario Sergio
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión aceptada
Descripción
The calculation of volume of different oilseed grains, through computational models, has demonstrated effectiveness and efficiency. In the present work, the model has been extended to allow calculations of the volume of soybeans. In the model is proposed each grain of the sample is assimilated to a parallelepiped with main axes L (length), W (width) and T (thickness). The L and W values are determined from the Feret distances of the image, and the thickness is assumed to be proportional to width of the grain. The proportionality constant k is calculated using the formula of the model and validated against the experimental volume of the samples, fielding a confidence or percentual relative deviation. The model developed approximates soybean volume with confidence of a 1.25% using low-cost hardware for image acquisition and moderate computational resources.
Fil: Villaverde, Jorge. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Centro de Investigación Aplicada en Tecnologías de la Información y Comunicación; Argentina.
Fil: Cleva, Mario Sergio. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Centro de Investigación Aplicada en Tecnologías de la Información y Comunicación; Argentina.
Peer Reviewed
Materia
Grain morphology
Feret distance
ImageJ
Nivel de accesibilidad
acceso abierto
Condiciones de uso
2024-03-23T13:28:20Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/10017
Acceder
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network_acronym_str RIAUTN
repository_id_str a
network_name_str Repositorio Institucional Abierto (UTN)
spelling Volume estimation of unbroken soybeans samples using digital image processing techniquesVillaverde, JorgeCleva, Mario SergioGrain morphologyFeret distanceImageJThe calculation of volume of different oilseed grains, through computational models, has demonstrated effectiveness and efficiency. In the present work, the model has been extended to allow calculations of the volume of soybeans. In the model is proposed each grain of the sample is assimilated to a parallelepiped with main axes L (length), W (width) and T (thickness). The L and W values are determined from the Feret distances of the image, and the thickness is assumed to be proportional to width of the grain. The proportionality constant k is calculated using the formula of the model and validated against the experimental volume of the samples, fielding a confidence or percentual relative deviation. The model developed approximates soybean volume with confidence of a 1.25% using low-cost hardware for image acquisition and moderate computational resources.Fil: Villaverde, Jorge. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Centro de Investigación Aplicada en Tecnologías de la Información y Comunicación; Argentina.Fil: Cleva, Mario Sergio. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Centro de Investigación Aplicada en Tecnologías de la Información y Comunicación; Argentina.Peer Reviewed2024-03-23T13:28:20Z2024-03-23T13:28:20Z2024-01-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdfRevista de Investigaciones Agropecuarias. RIA1669-2314http://hdl.handle.net/20.500.12272/10017engPAUTIRE0007650TCSistema experto de visión para la clasificación automática de la calidad de frutos/semillas de plantas oleaginosasinfo:eu-repo/semantics/openAccess2024-03-23T13:28:20Zhttp://creativecommons.org/licenses/by-nc-sa/4.0/Atribución-NoComercial-CompartirIgual 4.0 InternacionalAcceso abiertoreponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-10-01T11:57:13Zoai:ria.utn.edu.ar:20.500.12272/10017instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-10-01 11:57:13.855Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv Volume estimation of unbroken soybeans samples using digital image processing techniques
title Volume estimation of unbroken soybeans samples using digital image processing techniques
spellingShingle Volume estimation of unbroken soybeans samples using digital image processing techniques
Villaverde, Jorge
Grain morphology
Feret distance
ImageJ
title_short Volume estimation of unbroken soybeans samples using digital image processing techniques
title_full Volume estimation of unbroken soybeans samples using digital image processing techniques
title_fullStr Volume estimation of unbroken soybeans samples using digital image processing techniques
title_full_unstemmed Volume estimation of unbroken soybeans samples using digital image processing techniques
title_sort Volume estimation of unbroken soybeans samples using digital image processing techniques
dc.creator.none.fl_str_mv Villaverde, Jorge
Cleva, Mario Sergio
author Villaverde, Jorge
author_facet Villaverde, Jorge
Cleva, Mario Sergio
author_role author
author2 Cleva, Mario Sergio
author2_role author
dc.subject.none.fl_str_mv Grain morphology
Feret distance
ImageJ
topic Grain morphology
Feret distance
ImageJ
dc.description.none.fl_txt_mv The calculation of volume of different oilseed grains, through computational models, has demonstrated effectiveness and efficiency. In the present work, the model has been extended to allow calculations of the volume of soybeans. In the model is proposed each grain of the sample is assimilated to a parallelepiped with main axes L (length), W (width) and T (thickness). The L and W values are determined from the Feret distances of the image, and the thickness is assumed to be proportional to width of the grain. The proportionality constant k is calculated using the formula of the model and validated against the experimental volume of the samples, fielding a confidence or percentual relative deviation. The model developed approximates soybean volume with confidence of a 1.25% using low-cost hardware for image acquisition and moderate computational resources.
Fil: Villaverde, Jorge. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Centro de Investigación Aplicada en Tecnologías de la Información y Comunicación; Argentina.
Fil: Cleva, Mario Sergio. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Centro de Investigación Aplicada en Tecnologías de la Información y Comunicación; Argentina.
Peer Reviewed
description The calculation of volume of different oilseed grains, through computational models, has demonstrated effectiveness and efficiency. In the present work, the model has been extended to allow calculations of the volume of soybeans. In the model is proposed each grain of the sample is assimilated to a parallelepiped with main axes L (length), W (width) and T (thickness). The L and W values are determined from the Feret distances of the image, and the thickness is assumed to be proportional to width of the grain. The proportionality constant k is calculated using the formula of the model and validated against the experimental volume of the samples, fielding a confidence or percentual relative deviation. The model developed approximates soybean volume with confidence of a 1.25% using low-cost hardware for image acquisition and moderate computational resources.
publishDate 2024
dc.date.none.fl_str_mv 2024-03-23T13:28:20Z
2024-03-23T13:28:20Z
2024-01-24
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv Revista de Investigaciones Agropecuarias. RIA
1669-2314
http://hdl.handle.net/20.500.12272/10017
identifier_str_mv Revista de Investigaciones Agropecuarias. RIA
1669-2314
url http://hdl.handle.net/20.500.12272/10017
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv PAUTIRE0007650TC
Sistema experto de visión para la clasificación automática de la calidad de frutos/semillas de plantas oleaginosas
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2024-03-23T13:28:20Z
http://creativecommons.org/licenses/by-nc-sa/4.0/
Atribución-NoComercial-CompartirIgual 4.0 Internacional
Acceso abierto
eu_rights_str_mv openAccess
rights_invalid_str_mv 2024-03-23T13:28:20Z
http://creativecommons.org/licenses/by-nc-sa/4.0/
Atribución-NoComercial-CompartirIgual 4.0 Internacional
Acceso abierto
dc.format.none.fl_str_mv pdf
application/pdf
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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score 13.365483

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