Olive Ripening Phase Estimation based on Neural Networks
- Autores
- Mora, Marco; Aliaga, Jorge; Fredes, Claudio
- Año de publicación
- 2017
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Color of fruits is a relevant parameter to determine ripeness and optimal harvest time. For olives 6 ripening phases based on skin color distribution have been defined. A widely used method by the olive oil and table olives producers is to inspect the olive surface, and estimate the color and ripening phase visually. This method is simple but it is highly subjective and imprecise. This paper proposes a computational method to estimate the color and ripeness of an olive using digital images. A color scale for olives by means of samples of all ripening phases was developed. To represent the olive color, the histogram of the skin color was proposed as a descriptor. To decide the ripening phase, a classifier based on Neural Networks was implemented. The method allows estimating simply and accurately the olive ripening state, which enables to implement it in real production systems.
Sociedad Argentina de Informática e Investigación Operativa (SADIO) - Materia
-
Ciencias Informáticas
olive ripening phases
color histogram
neural networks - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-sa/3.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/62909
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Olive Ripening Phase Estimation based on Neural NetworksMora, MarcoAliaga, JorgeFredes, ClaudioCiencias Informáticasolive ripening phasescolor histogramneural networksColor of fruits is a relevant parameter to determine ripeness and optimal harvest time. For olives 6 ripening phases based on skin color distribution have been defined. A widely used method by the olive oil and table olives producers is to inspect the olive surface, and estimate the color and ripening phase visually. This method is simple but it is highly subjective and imprecise. This paper proposes a computational method to estimate the color and ripeness of an olive using digital images. A color scale for olives by means of samples of all ripening phases was developed. To represent the olive color, the histogram of the skin color was proposed as a descriptor. To decide the ripening phase, a classifier based on Neural Networks was implemented. The method allows estimating simply and accurately the olive ripening state, which enables to implement it in real production systems.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2017-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf127-140http://sedici.unlp.edu.ar/handle/10915/62909enginfo:eu-repo/semantics/altIdentifier/url/http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/CAI/CAI-12.pdfinfo:eu-repo/semantics/altIdentifier/issn/2525- 0949info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:08:14Zoai:sedici.unlp.edu.ar:10915/62909Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:08:15.099SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Olive Ripening Phase Estimation based on Neural Networks |
title |
Olive Ripening Phase Estimation based on Neural Networks |
spellingShingle |
Olive Ripening Phase Estimation based on Neural Networks Mora, Marco Ciencias Informáticas olive ripening phases color histogram neural networks |
title_short |
Olive Ripening Phase Estimation based on Neural Networks |
title_full |
Olive Ripening Phase Estimation based on Neural Networks |
title_fullStr |
Olive Ripening Phase Estimation based on Neural Networks |
title_full_unstemmed |
Olive Ripening Phase Estimation based on Neural Networks |
title_sort |
Olive Ripening Phase Estimation based on Neural Networks |
dc.creator.none.fl_str_mv |
Mora, Marco Aliaga, Jorge Fredes, Claudio |
author |
Mora, Marco |
author_facet |
Mora, Marco Aliaga, Jorge Fredes, Claudio |
author_role |
author |
author2 |
Aliaga, Jorge Fredes, Claudio |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas olive ripening phases color histogram neural networks |
topic |
Ciencias Informáticas olive ripening phases color histogram neural networks |
dc.description.none.fl_txt_mv |
Color of fruits is a relevant parameter to determine ripeness and optimal harvest time. For olives 6 ripening phases based on skin color distribution have been defined. A widely used method by the olive oil and table olives producers is to inspect the olive surface, and estimate the color and ripening phase visually. This method is simple but it is highly subjective and imprecise. This paper proposes a computational method to estimate the color and ripeness of an olive using digital images. A color scale for olives by means of samples of all ripening phases was developed. To represent the olive color, the histogram of the skin color was proposed as a descriptor. To decide the ripening phase, a classifier based on Neural Networks was implemented. The method allows estimating simply and accurately the olive ripening state, which enables to implement it in real production systems. Sociedad Argentina de Informática e Investigación Operativa (SADIO) |
description |
Color of fruits is a relevant parameter to determine ripeness and optimal harvest time. For olives 6 ripening phases based on skin color distribution have been defined. A widely used method by the olive oil and table olives producers is to inspect the olive surface, and estimate the color and ripening phase visually. This method is simple but it is highly subjective and imprecise. This paper proposes a computational method to estimate the color and ripeness of an olive using digital images. A color scale for olives by means of samples of all ripening phases was developed. To represent the olive color, the histogram of the skin color was proposed as a descriptor. To decide the ripening phase, a classifier based on Neural Networks was implemented. The method allows estimating simply and accurately the olive ripening state, which enables to implement it in real production systems. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-09 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/62909 |
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http://sedici.unlp.edu.ar/handle/10915/62909 |
dc.language.none.fl_str_mv |
eng |
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eng |
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dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-sa/3.0/ Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) |
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openAccess |
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http://creativecommons.org/licenses/by-sa/3.0/ Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) |
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application/pdf 127-140 |
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