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Artificial Vision Techniques to Optimize Strawberry's Industrial Classification.

This research presents novel artificial vision techniques applied to the detection of features for strawberries used in the food industry. For this purpose, a computer vision system based in artificial neural networks is used, organized as a deep architecture and trained with noise compensated learn...

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Autor Principal: Chang Tortolero, Oscar Guillermo
Formato: Artículos
Lenguaje:eng
Publicado: 2017
Materias:
WEBCAMS
COLOR
NEURAL NETWORKS
Acceso en línea:http://repositorio.educacionsuperior.gob.ec/handle/28000/3866
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spelling oai:localhost:28000-38662017-04-13T08:02:22Z Artificial Vision Techniques to Optimize Strawberry's Industrial Classification. Chang Tortolero, Oscar Guillermo WEBCAMS COLOR NEURAL NETWORKS This research presents novel artificial vision techniques applied to the detection of features for strawberries used in the food industry. For this purpose, a computer vision system based in artificial neural networks is used, organized as a deep architecture and trained with noise compensated learning. This combination originates a strong network - object relations which makes possible the recognition of complex strawberry features under changing conditions of lightning, size and orientation. The programming uses OpenCV libraries and fruits databases captured with a webcam. The images used to train the Artificial Neural Network are defined with canny edge detection and a moving region of interest (ROI). After training, the network recognizes important features such as shape, color and anomalies. The system has been tested in real time with real images. 2017-04-12T17:59:33Z 2017-04-12T17:59:33Z 2016 article Constante. P. et al. (2016). Artificial Vision Techniques to Optimize Strawberry's Industrial Classification. IEEE Latin America Transactions. Vol. 14. 1548-0992 http://repositorio.educacionsuperior.gob.ec/handle/28000/3866 eng DOI;10.1109/TLA.2016.7555221 closedAccess
institution SENESCYT
collection Repositorio SENESCYT
biblioteca Biblioteca Senescyt
language eng
format Artículos
topic WEBCAMS
COLOR
NEURAL NETWORKS
spellingShingle WEBCAMS
COLOR
NEURAL NETWORKS
Chang Tortolero, Oscar Guillermo
Artificial Vision Techniques to Optimize Strawberry's Industrial Classification.
description This research presents novel artificial vision techniques applied to the detection of features for strawberries used in the food industry. For this purpose, a computer vision system based in artificial neural networks is used, organized as a deep architecture and trained with noise compensated learning. This combination originates a strong network - object relations which makes possible the recognition of complex strawberry features under changing conditions of lightning, size and orientation. The programming uses OpenCV libraries and fruits databases captured with a webcam. The images used to train the Artificial Neural Network are defined with canny edge detection and a moving region of interest (ROI). After training, the network recognizes important features such as shape, color and anomalies. The system has been tested in real time with real images.
author Chang Tortolero, Oscar Guillermo
author_facet Chang Tortolero, Oscar Guillermo
author_sort Chang Tortolero, Oscar Guillermo
title Artificial Vision Techniques to Optimize Strawberry's Industrial Classification.
title_short Artificial Vision Techniques to Optimize Strawberry's Industrial Classification.
title_full Artificial Vision Techniques to Optimize Strawberry's Industrial Classification.
title_fullStr Artificial Vision Techniques to Optimize Strawberry's Industrial Classification.
title_full_unstemmed Artificial Vision Techniques to Optimize Strawberry's Industrial Classification.
title_sort artificial vision techniques to optimize strawberry's industrial classification.
publishDate 2017
url http://repositorio.educacionsuperior.gob.ec/handle/28000/3866
_version_ 1634995197546856448
score 11,871979

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