EXTRACTION OF SIMPLE ROAD CROSSING
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/196066 |
Resumo: | Road crossings of roads are important components of the road network. However, they generally are not explicit in the existing research on extraction of road network. This is due to the wide variety of road crossings may contain. Thus this paper presents a methodology for the extraction of simples road crossings considering the stages of pre-processing that performs a smoothing of the region of crossing, followed by binarization and skeletonization of the region of road crossing. Soon after the methodology proposes a model skeleton to perform a filtering of the spurious structures. Based on the model filtered performs the extraction of the edges of road crossings. The methodology was evaluated for four images with respect to the criterion of completeness and proved to be quite effective in content page 83.5% completeness of the average images. |
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Repositório Institucional da UNESP |
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EXTRACTION OF SIMPLE ROAD CROSSINGRoad CrossingRoad SeedsSegmentation of region crossingsSkeletonizationRoad crossings of roads are important components of the road network. However, they generally are not explicit in the existing research on extraction of road network. This is due to the wide variety of road crossings may contain. Thus this paper presents a methodology for the extraction of simples road crossings considering the stages of pre-processing that performs a smoothing of the region of crossing, followed by binarization and skeletonization of the region of road crossing. Soon after the methodology proposes a model skeleton to perform a filtering of the spurious structures. Based on the model filtered performs the extraction of the edges of road crossings. The methodology was evaluated for four images with respect to the criterion of completeness and proved to be quite effective in content page 83.5% completeness of the average images.State University of Sao Paulo (UNESP)State University of Mato Grosso (UNEMAT)Foundation of Research of State Mato Grosso (FAPEMAT)Univ Estado Mato Grosso, UNEMAT, Dept Math, Sinop, BrazilUniv Estado Mato Grosso, UNEMAT, Dept Comp, Colider, BrazilState Univ Sao Paulo, UNESP, Dept Cartog, Sao Paulo, BrazilState Univ Sao Paulo, UNESP, Dept Cartog, Sao Paulo, BrazilCopernicus Gesellschaft MbhUniv Estado Mato GrossoUniversidade Estadual Paulista (Unesp)Zanin, R. B.Martins, E. F. O.Vale, G. M. doDal Poz, A. P. [UNESP]Paparoditis, N.PierrotDeseilligny, M.Mallet, C.Tournaire, O.2020-12-10T19:32:12Z2020-12-10T19:32:12Z2010-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject55-59Pcv 2010: Photogrammetric Computer Vision And Image Analysis, Pt Ii. Gottingen: Copernicus Gesellschaft Mbh, v. 38, p. 55-59, 2010.2194-9034http://hdl.handle.net/11449/196066WOS:000345370800011Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPcv 2010: Photogrammetric Computer Vision And Image Analysis, Pt Iiinfo:eu-repo/semantics/openAccess2024-06-18T15:02:41Zoai:repositorio.unesp.br:11449/196066Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:48:21.597876Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
EXTRACTION OF SIMPLE ROAD CROSSING |
title |
EXTRACTION OF SIMPLE ROAD CROSSING |
spellingShingle |
EXTRACTION OF SIMPLE ROAD CROSSING Zanin, R. B. Road Crossing Road Seeds Segmentation of region crossings Skeletonization |
title_short |
EXTRACTION OF SIMPLE ROAD CROSSING |
title_full |
EXTRACTION OF SIMPLE ROAD CROSSING |
title_fullStr |
EXTRACTION OF SIMPLE ROAD CROSSING |
title_full_unstemmed |
EXTRACTION OF SIMPLE ROAD CROSSING |
title_sort |
EXTRACTION OF SIMPLE ROAD CROSSING |
author |
Zanin, R. B. |
author_facet |
Zanin, R. B. Martins, E. F. O. Vale, G. M. do Dal Poz, A. P. [UNESP] Paparoditis, N. PierrotDeseilligny, M. Mallet, C. Tournaire, O. |
author_role |
author |
author2 |
Martins, E. F. O. Vale, G. M. do Dal Poz, A. P. [UNESP] Paparoditis, N. PierrotDeseilligny, M. Mallet, C. Tournaire, O. |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Univ Estado Mato Grosso Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Zanin, R. B. Martins, E. F. O. Vale, G. M. do Dal Poz, A. P. [UNESP] Paparoditis, N. PierrotDeseilligny, M. Mallet, C. Tournaire, O. |
dc.subject.por.fl_str_mv |
Road Crossing Road Seeds Segmentation of region crossings Skeletonization |
topic |
Road Crossing Road Seeds Segmentation of region crossings Skeletonization |
description |
Road crossings of roads are important components of the road network. However, they generally are not explicit in the existing research on extraction of road network. This is due to the wide variety of road crossings may contain. Thus this paper presents a methodology for the extraction of simples road crossings considering the stages of pre-processing that performs a smoothing of the region of crossing, followed by binarization and skeletonization of the region of road crossing. Soon after the methodology proposes a model skeleton to perform a filtering of the spurious structures. Based on the model filtered performs the extraction of the edges of road crossings. The methodology was evaluated for four images with respect to the criterion of completeness and proved to be quite effective in content page 83.5% completeness of the average images. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-01-01 2020-12-10T19:32:12Z 2020-12-10T19:32:12Z |
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 |
Pcv 2010: Photogrammetric Computer Vision And Image Analysis, Pt Ii. Gottingen: Copernicus Gesellschaft Mbh, v. 38, p. 55-59, 2010. 2194-9034 http://hdl.handle.net/11449/196066 WOS:000345370800011 |
identifier_str_mv |
Pcv 2010: Photogrammetric Computer Vision And Image Analysis, Pt Ii. Gottingen: Copernicus Gesellschaft Mbh, v. 38, p. 55-59, 2010. 2194-9034 WOS:000345370800011 |
url |
http://hdl.handle.net/11449/196066 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Pcv 2010: Photogrammetric Computer Vision And Image Analysis, Pt Ii |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
55-59 |
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_ |
1808129463213359104 |