An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation

Autores
Jordan, Mario Alberto; Trabes, Emanuel
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This work aims the design and implementation of an adaptive vision-based sensor for detecting a pipe on underwater scenes in real time. The motivation is focused to future applications of vision servo control in underwater vehicles. The approach employs color and shape image segmentation together with an adjust mechanism that aims continuously in time to reach the best setup of a parameter set of the color image segmentation. The sensor performs very well even in the case of large and rapid changes in the scene illumination. On the basis of many experiments carried out in real scenes and the comparison with similar algorithms in the state-of-the-art field on the same application, the approach gets a better positioning with respect to related results above all in the case of extremely changing and poor luminance conditions. As drawback, the required computation time to achieve optimal values for the first time (auto-tuning phase) may be large; contrary to the adaptive ongoing process, in where the optimization is much more agile.
Fil: Jordan, Mario Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; Argentina
Fil: Trabes, Emanuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina
Materia
underwater pipeline detection
vision-based sensor
HSV model
optimal parameter adjustments
chanching illumination levels
adaptative sensor
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/12571
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image SegmentationJordan, Mario AlbertoTrabes, Emanuelunderwater pipeline detectionvision-based sensorHSV modeloptimal parameter adjustmentschanching illumination levelsadaptative sensorhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2This work aims the design and implementation of an adaptive vision-based sensor for detecting a pipe on underwater scenes in real time. The motivation is focused to future applications of vision servo control in underwater vehicles. The approach employs color and shape image segmentation together with an adjust mechanism that aims continuously in time to reach the best setup of a parameter set of the color image segmentation. The sensor performs very well even in the case of large and rapid changes in the scene illumination. On the basis of many experiments carried out in real scenes and the comparison with similar algorithms in the state-of-the-art field on the same application, the approach gets a better positioning with respect to related results above all in the case of extremely changing and poor luminance conditions. As drawback, the required computation time to achieve optimal values for the first time (auto-tuning phase) may be large; contrary to the adaptive ongoing process, in where the optimization is much more agile.Fil: Jordan, Mario Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Trabes, Emanuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); ArgentinaScience and Engineering Institute2015-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/12571Jordan, Mario Alberto; Trabes, Emanuel; An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation; Science and Engineering Institute; Journal of Automation and Control Engineering; 3; 6; 4-2015; 480-4862301-37022325-7415enginfo:eu-repo/semantics/altIdentifier/url/http://www.joace.org/index.php?m=content&c=index&a=show&catid=50&id=278info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:31:09Zoai:ri.conicet.gov.ar:11336/12571instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:31:10.148CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation
title An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation
spellingShingle An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation
Jordan, Mario Alberto
underwater pipeline detection
vision-based sensor
HSV model
optimal parameter adjustments
chanching illumination levels
adaptative sensor
title_short An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation
title_full An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation
title_fullStr An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation
title_full_unstemmed An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation
title_sort An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation
dc.creator.none.fl_str_mv Jordan, Mario Alberto
Trabes, Emanuel
author Jordan, Mario Alberto
author_facet Jordan, Mario Alberto
Trabes, Emanuel
author_role author
author2 Trabes, Emanuel
author2_role author
dc.subject.none.fl_str_mv underwater pipeline detection
vision-based sensor
HSV model
optimal parameter adjustments
chanching illumination levels
adaptative sensor
topic underwater pipeline detection
vision-based sensor
HSV model
optimal parameter adjustments
chanching illumination levels
adaptative sensor
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This work aims the design and implementation of an adaptive vision-based sensor for detecting a pipe on underwater scenes in real time. The motivation is focused to future applications of vision servo control in underwater vehicles. The approach employs color and shape image segmentation together with an adjust mechanism that aims continuously in time to reach the best setup of a parameter set of the color image segmentation. The sensor performs very well even in the case of large and rapid changes in the scene illumination. On the basis of many experiments carried out in real scenes and the comparison with similar algorithms in the state-of-the-art field on the same application, the approach gets a better positioning with respect to related results above all in the case of extremely changing and poor luminance conditions. As drawback, the required computation time to achieve optimal values for the first time (auto-tuning phase) may be large; contrary to the adaptive ongoing process, in where the optimization is much more agile.
Fil: Jordan, Mario Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; Argentina
Fil: Trabes, Emanuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina
description This work aims the design and implementation of an adaptive vision-based sensor for detecting a pipe on underwater scenes in real time. The motivation is focused to future applications of vision servo control in underwater vehicles. The approach employs color and shape image segmentation together with an adjust mechanism that aims continuously in time to reach the best setup of a parameter set of the color image segmentation. The sensor performs very well even in the case of large and rapid changes in the scene illumination. On the basis of many experiments carried out in real scenes and the comparison with similar algorithms in the state-of-the-art field on the same application, the approach gets a better positioning with respect to related results above all in the case of extremely changing and poor luminance conditions. As drawback, the required computation time to achieve optimal values for the first time (auto-tuning phase) may be large; contrary to the adaptive ongoing process, in where the optimization is much more agile.
publishDate 2015
dc.date.none.fl_str_mv 2015-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/12571
Jordan, Mario Alberto; Trabes, Emanuel; An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation; Science and Engineering Institute; Journal of Automation and Control Engineering; 3; 6; 4-2015; 480-486
2301-3702
2325-7415
url http://hdl.handle.net/11336/12571
identifier_str_mv Jordan, Mario Alberto; Trabes, Emanuel; An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation; Science and Engineering Institute; Journal of Automation and Control Engineering; 3; 6; 4-2015; 480-486
2301-3702
2325-7415
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.joace.org/index.php?m=content&c=index&a=show&catid=50&id=278
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Science and Engineering Institute
publisher.none.fl_str_mv Science and Engineering Institute
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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