Road region detection in urban areas combining high-resolution RGB image and laser scanning data in a classification framework
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/227944 |
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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Repositório Institucional da UNESP |
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2946 |
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Road region detection in urban areas combining high-resolution RGB image and laser scanning data in a classification frameworkArtificial Neural NetworkLaser pulse intensity imageNormalized digital surface modelRGB aerial 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.Dept. of Cartography, São Paulo State University, R. Roberto Simonsen, 305Dept. of Cartography, São Paulo State University, R. Roberto Simonsen, 305Universidade Estadual Paulista (UNESP)Poz, A.P. Dal [UNESP]Mendes, T. S.G. [UNESP]2022-04-29T07:25:55Z2022-04-29T07:25:55Z2013-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject53-56International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, v. 40, n. 1W1, p. 53-56, 2013.1682-1750http://hdl.handle.net/11449/2279442-s2.0-84924691822Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archivesinfo:eu-repo/semantics/openAccess2024-06-18T15:02:40Zoai:repositorio.unesp.br:11449/227944Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:47:02.424543Repositório 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 Poz, A.P. Dal [UNESP] Artificial Neural Network Laser pulse intensity image Normalized digital surface model RGB aerial 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 |
Poz, A.P. Dal [UNESP] |
author_facet |
Poz, A.P. Dal [UNESP] Mendes, T. S.G. [UNESP] |
author_role |
author |
author2 |
Mendes, T. S.G. [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Poz, A.P. Dal [UNESP] Mendes, T. S.G. [UNESP] |
dc.subject.por.fl_str_mv |
Artificial Neural Network Laser pulse intensity image Normalized digital surface model RGB aerial image |
topic |
Artificial Neural Network Laser pulse intensity image Normalized digital surface model RGB aerial 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 2022-04-29T07:25:55Z 2022-04-29T07:25:55Z |
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 |
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, v. 40, n. 1W1, p. 53-56, 2013. 1682-1750 http://hdl.handle.net/11449/227944 2-s2.0-84924691822 |
identifier_str_mv |
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, v. 40, n. 1W1, p. 53-56, 2013. 1682-1750 2-s2.0-84924691822 |
url |
http://hdl.handle.net/11449/227944 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
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.source.none.fl_str_mv |
Scopus 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_ |
1808129247383912448 |