ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK

Detalhes bibliográficos
Autor(a) principal: Dal Poz, A. P. [UNESP]
Data de Publicação: 2013
Outros Autores: Mendes, T. S. G. [UNESP], Heipke, C., Jacobsen, K., Rottensteiner, F., Sorgel, U.
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/196079
Resumo: This paper addresses the problem of road region detection in urban areas using an image classification approach. In order to minimize the spectral superposition of the road (asphalt) class with other classes, the Artificial Neural Networks (ANN) image classification method was used to classify geometrically-integrated high-resolution RGB aerial and laser-derived images. The RGB image was combined with different laser data layers and the ANN classification results showed that the radiometric and geometric laser data allows a better detection of road pixel.
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spelling ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORKArtificial Neural NetworkRGB Aerial ImageNormalized Digital Surface ModelLaser Pulse Intensity ImageThis paper addresses the problem of road region detection in urban areas using an image classification approach. In order to minimize the spectral superposition of the road (asphalt) class with other classes, the Artificial Neural Networks (ANN) image classification method was used to classify geometrically-integrated high-resolution RGB aerial and laser-derived images. The RGB image was combined with different laser data layers and the ANN classification results showed that the radiometric and geometric laser data allows a better detection of road pixel.Sao Paulo State Univ, Dept Cartog, Presidente Prudente, SP, BrazilSao Paulo State Univ, Dept Cartog, Presidente Prudente, SP, BrazilCopernicus Gesellschaft MbhUniversidade Estadual Paulista (Unesp)Dal Poz, A. P. [UNESP]Mendes, T. S. G. [UNESP]Heipke, C.Jacobsen, K.Rottensteiner, F.Sorgel, U.2020-12-10T19:32:38Z2020-12-10T19:32:38Z2013-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject53-56Isprs Hannover Workshop 2013. Gottingen: Copernicus Gesellschaft Mbh, v. 40-1, n. W-1, p. 53-56, 2013.2194-9034http://hdl.handle.net/11449/196079WOS:000358215100010Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIsprs Hannover Workshop 2013info:eu-repo/semantics/openAccess2024-06-18T15:02:39Zoai:repositorio.unesp.br:11449/196079Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:11:21.987475Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK
title ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK
spellingShingle ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK
Dal Poz, A. P. [UNESP]
Artificial Neural Network
RGB Aerial Image
Normalized Digital Surface Model
Laser Pulse Intensity Image
title_short ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK
title_full ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK
title_fullStr ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK
title_full_unstemmed ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK
title_sort ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK
author Dal Poz, A. P. [UNESP]
author_facet Dal Poz, A. P. [UNESP]
Mendes, T. S. G. [UNESP]
Heipke, C.
Jacobsen, K.
Rottensteiner, F.
Sorgel, U.
author_role author
author2 Mendes, T. S. G. [UNESP]
Heipke, C.
Jacobsen, K.
Rottensteiner, F.
Sorgel, U.
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Dal Poz, A. P. [UNESP]
Mendes, T. S. G. [UNESP]
Heipke, C.
Jacobsen, K.
Rottensteiner, F.
Sorgel, U.
dc.subject.por.fl_str_mv Artificial Neural Network
RGB Aerial Image
Normalized Digital Surface Model
Laser Pulse Intensity Image
topic Artificial Neural Network
RGB Aerial Image
Normalized Digital Surface Model
Laser Pulse Intensity Image
description This paper addresses the problem of road region detection in urban areas using an image classification approach. In order to minimize the spectral superposition of the road (asphalt) class with other classes, the Artificial Neural Networks (ANN) image classification method was used to classify geometrically-integrated high-resolution RGB aerial and laser-derived images. The RGB image was combined with different laser data layers and the ANN classification results showed that the radiometric and geometric laser data allows a better detection of road pixel.
publishDate 2013
dc.date.none.fl_str_mv 2013-01-01
2020-12-10T19:32:38Z
2020-12-10T19:32:38Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv Isprs Hannover Workshop 2013. Gottingen: Copernicus Gesellschaft Mbh, v. 40-1, n. W-1, p. 53-56, 2013.
2194-9034
http://hdl.handle.net/11449/196079
WOS:000358215100010
identifier_str_mv Isprs Hannover Workshop 2013. Gottingen: Copernicus Gesellschaft Mbh, v. 40-1, n. W-1, p. 53-56, 2013.
2194-9034
WOS:000358215100010
url http://hdl.handle.net/11449/196079
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Isprs Hannover Workshop 2013
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 53-56
dc.publisher.none.fl_str_mv Copernicus Gesellschaft Mbh
publisher.none.fl_str_mv Copernicus Gesellschaft Mbh
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808129169528193024

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