Street region detection from normalized Digital Surface Model and laser data intensity image
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/227939 |
Resumo: | The urban road network extraction process can be simplified by firstly detecting regions corresponding to streets, allowing a substantial reduction of the search area. As a result, the extraction process is benefited in two aspects: the computational complexity and the reliability. This paper aims at detecting street regions using only data obtained by Laser Scanner Systems. A sequence of standard image processing techniques is used to process height and intensity laser scanner data. A normalized Digital Surface Model is derived from height laser scanner data, from which regions corresponding to aboveground objects (mainly trees and buildings) are detected. Next, detected tree regions are eliminated from the aboveground regions, remaining only buildings. Then, morphological operators are applied in order to obtain elongated street ribbons and homogeneous block regions. Street regions are also detected in the intensity image. The results obtained from the radiometric and geometric laser scanner data are combined, allowing the elimination of non-street regions and the improvement of the geometry of region boundaries. The experimental results showed that the methodology proved to be efficient to detect street regions. |
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Repositório Institucional da UNESP |
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Street region detection from normalized Digital Surface Model and laser data intensity imageImage processing techniquesIntensity imageLaser scanner dataNormalized digital surface modelStreet region detectionThe urban road network extraction process can be simplified by firstly detecting regions corresponding to streets, allowing a substantial reduction of the search area. As a result, the extraction process is benefited in two aspects: the computational complexity and the reliability. This paper aims at detecting street regions using only data obtained by Laser Scanner Systems. A sequence of standard image processing techniques is used to process height and intensity laser scanner data. A normalized Digital Surface Model is derived from height laser scanner data, from which regions corresponding to aboveground objects (mainly trees and buildings) are detected. Next, detected tree regions are eliminated from the aboveground regions, remaining only buildings. Then, morphological operators are applied in order to obtain elongated street ribbons and homogeneous block regions. Street regions are also detected in the intensity image. The results obtained from the radiometric and geometric laser scanner data are combined, allowing the elimination of non-street regions and the improvement of the geometry of region boundaries. The experimental results showed that the methodology proved to be efficient to detect street regions.UNESP São Paulo State University Cartographic Sciences Graduate ProgramUNESP São Paulo State University Department of CartographyUNESP São Paulo State University Cartographic Sciences Graduate ProgramUNESP São Paulo State University Department of CartographyUniversidade Estadual Paulista (UNESP)Mendes, T. S.G. [UNESP]Dal Poz, A. P. [UNESP]2022-04-29T07:25:54Z2022-04-29T07:25:54Z2011-04-26info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject197-202International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, v. 38, n. 3W22, p. 197-202, 2011.1682-1750http://hdl.handle.net/11449/2279392-s2.0-84923911572Scopusreponame: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:11449/227939Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-06-18T15:02:40Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Street region detection from normalized Digital Surface Model and laser data intensity image |
title |
Street region detection from normalized Digital Surface Model and laser data intensity image |
spellingShingle |
Street region detection from normalized Digital Surface Model and laser data intensity image Mendes, T. S.G. [UNESP] Image processing techniques Intensity image Laser scanner data Normalized digital surface model Street region detection |
title_short |
Street region detection from normalized Digital Surface Model and laser data intensity image |
title_full |
Street region detection from normalized Digital Surface Model and laser data intensity image |
title_fullStr |
Street region detection from normalized Digital Surface Model and laser data intensity image |
title_full_unstemmed |
Street region detection from normalized Digital Surface Model and laser data intensity image |
title_sort |
Street region detection from normalized Digital Surface Model and laser data intensity image |
author |
Mendes, T. S.G. [UNESP] |
author_facet |
Mendes, T. S.G. [UNESP] Dal Poz, A. P. [UNESP] |
author_role |
author |
author2 |
Dal Poz, A. P. [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Mendes, T. S.G. [UNESP] Dal Poz, A. P. [UNESP] |
dc.subject.por.fl_str_mv |
Image processing techniques Intensity image Laser scanner data Normalized digital surface model Street region detection |
topic |
Image processing techniques Intensity image Laser scanner data Normalized digital surface model Street region detection |
description |
The urban road network extraction process can be simplified by firstly detecting regions corresponding to streets, allowing a substantial reduction of the search area. As a result, the extraction process is benefited in two aspects: the computational complexity and the reliability. This paper aims at detecting street regions using only data obtained by Laser Scanner Systems. A sequence of standard image processing techniques is used to process height and intensity laser scanner data. A normalized Digital Surface Model is derived from height laser scanner data, from which regions corresponding to aboveground objects (mainly trees and buildings) are detected. Next, detected tree regions are eliminated from the aboveground regions, remaining only buildings. Then, morphological operators are applied in order to obtain elongated street ribbons and homogeneous block regions. Street regions are also detected in the intensity image. The results obtained from the radiometric and geometric laser scanner data are combined, allowing the elimination of non-street regions and the improvement of the geometry of region boundaries. The experimental results showed that the methodology proved to be efficient to detect street regions. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-04-26 2022-04-29T07:25:54Z 2022-04-29T07:25:54Z |
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. 38, n. 3W22, p. 197-202, 2011. 1682-1750 http://hdl.handle.net/11449/227939 2-s2.0-84923911572 |
identifier_str_mv |
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, v. 38, n. 3W22, p. 197-202, 2011. 1682-1750 2-s2.0-84923911572 |
url |
http://hdl.handle.net/11449/227939 |
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 |
197-202 |
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_ |
1803045453783105536 |