Artificial neural network color-based positioning system for multiple objects underwater

Tracking objects underwater is a very hard task because of the hostile environment that the water presents. Many parameters should be considered in order to lessen the effect of the hostility. Such parameters underwater are not considered in the vision tracking and/or positioning of objects underwat...

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Main Authors: Delos Santos, Cyrus M., Dadios, Elmer P.
Format: text
Published: Animo Repository 2012
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/1901
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-29002021-07-30T01:11:29Z Artificial neural network color-based positioning system for multiple objects underwater Delos Santos, Cyrus M. Dadios, Elmer P. Tracking objects underwater is a very hard task because of the hostile environment that the water presents. Many parameters should be considered in order to lessen the effect of the hostility. Such parameters underwater are not considered in the vision tracking and/or positioning of objects underwater as long as the image taken is not that distorted. This study proposes an image-based positioning system using neural network for colored objects submerged underwater. The sample data for the Artificial Neural Network model is gathered by empirical methods using actual experimental set-up. The neural network is represented by the following variables: HSI components and panning values as inputs and the coordinates of each colored objects as outputs. © 2012 IEEE. 2012-12-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/1901 Faculty Research Work Animo Repository Neural networks (Computer science) Tracking (Engineering) Underwater imaging systems Underwater exploration Manufacturing
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Neural networks (Computer science)
Tracking (Engineering)
Underwater imaging systems
Underwater exploration
Manufacturing
spellingShingle Neural networks (Computer science)
Tracking (Engineering)
Underwater imaging systems
Underwater exploration
Manufacturing
Delos Santos, Cyrus M.
Dadios, Elmer P.
Artificial neural network color-based positioning system for multiple objects underwater
description Tracking objects underwater is a very hard task because of the hostile environment that the water presents. Many parameters should be considered in order to lessen the effect of the hostility. Such parameters underwater are not considered in the vision tracking and/or positioning of objects underwater as long as the image taken is not that distorted. This study proposes an image-based positioning system using neural network for colored objects submerged underwater. The sample data for the Artificial Neural Network model is gathered by empirical methods using actual experimental set-up. The neural network is represented by the following variables: HSI components and panning values as inputs and the coordinates of each colored objects as outputs. © 2012 IEEE.
format text
author Delos Santos, Cyrus M.
Dadios, Elmer P.
author_facet Delos Santos, Cyrus M.
Dadios, Elmer P.
author_sort Delos Santos, Cyrus M.
title Artificial neural network color-based positioning system for multiple objects underwater
title_short Artificial neural network color-based positioning system for multiple objects underwater
title_full Artificial neural network color-based positioning system for multiple objects underwater
title_fullStr Artificial neural network color-based positioning system for multiple objects underwater
title_full_unstemmed Artificial neural network color-based positioning system for multiple objects underwater
title_sort artificial neural network color-based positioning system for multiple objects underwater
publisher Animo Repository
publishDate 2012
url https://animorepository.dlsu.edu.ph/faculty_research/1901
_version_ 1707059170602123264