Olive Ripening Phase Estimation based on Neural Networks

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 ripeni...

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Detalles Bibliográficos
Autores principales:	Mora, Marco, Aliaga, Jorge, Fredes, Claudio
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2017
Materias:	Ciencias Informáticas olive ripening phases color histogram neural networks
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/62909 http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/CAI/CAI-12.pdf
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-62909
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas olive ripening phases color histogram neural networks
spellingShingle	Ciencias Informáticas olive ripening phases color histogram neural networks Mora, Marco Aliaga, Jorge Fredes, Claudio Olive Ripening Phase Estimation based on Neural Networks
topic_facet	Ciencias Informáticas olive ripening phases color histogram neural networks
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.
format	Objeto de conferencia Objeto de conferencia
author	Mora, Marco Aliaga, Jorge Fredes, Claudio
author_facet	Mora, Marco Aliaga, Jorge Fredes, Claudio
author_sort	Mora, Marco
title	Olive Ripening Phase Estimation based on 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
publishDate	2017
url	http://sedici.unlp.edu.ar/handle/10915/62909 http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/CAI/CAI-12.pdf
work_keys_str_mv	AT moramarco oliveripeningphaseestimationbasedonneuralnetworks AT aliagajorge oliveripeningphaseestimationbasedonneuralnetworks AT fredesclaudio oliveripeningphaseestimationbasedonneuralnetworks
bdutipo_str	Repositorios
_version_	1764820480118751233

Olive Ripening Phase Estimation based on Neural Networks

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