TSRS - A new approach for traffic sign recognition using the sift algorithm
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
DOI: | 10.4090/juee.2019.v13n1.059068 |
Texto Completo: | http://dx.doi.org/10.4090/juee.2019.v13n1.059068 http://hdl.handle.net/11449/199511 |
Resumo: | This paper proposes a new approach for traffic sign recognition using images captured by a low-cost mapping system. The proposed approach applies the SIFT algorithm to extract keypoint features that are used to evaluate the correspondences between a road image containing one or more plates and the images of traffic signs (templates). The BBF algorithm was used to efficiently evaluate the correspondence between the SIFT features. Finally, we propose a new algorithm to filter only the pairs of keypoints (image-template) that are compatible as well as the orientation and positioning. |
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Repositório Institucional da UNESP |
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2946 |
spelling |
TSRS - A new approach for traffic sign recognition using the sift algorithmCharacter recognitionRANSACSIFTTraffic sign recognitionThis paper proposes a new approach for traffic sign recognition using images captured by a low-cost mapping system. The proposed approach applies the SIFT algorithm to extract keypoint features that are used to evaluate the correspondences between a road image containing one or more plates and the images of traffic signs (templates). The BBF algorithm was used to efficiently evaluate the correspondence between the SIFT features. Finally, we propose a new algorithm to filter only the pairs of keypoints (image-template) that are compatible as well as the orientation and positioning.Department of Computer Science University of Western São Paulo (Unoeste)Department of Cartography Faculty of Science and Technology São Paulo State University (Unesp)Department of Mathematics and Computer Science Faculty of Science and Technology São Paulo State University (Unesp)Department of Cartography Faculty of Science and Technology São Paulo State University (Unesp)Department of Mathematics and Computer Science Faculty of Science and Technology São Paulo State University (Unesp)University of Western São Paulo (Unoeste)Universidade Estadual Paulista (Unesp)Silva, Francisco A.Pereira, Danillo R.Silva, João F. C. [UNESP]Artero, Almir O. [UNESP]Piteri, Marco A. [UNESP]2020-12-12T01:41:54Z2020-12-12T01:41:54Z2019-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article59-68http://dx.doi.org/10.4090/juee.2019.v13n1.059068Journal of Urban and Environmental Engineering, v. 13, n. 1, p. 59-68, 2019.1982-3932http://hdl.handle.net/11449/19951110.4090/juee.2019.v13n1.0590682-s2.0-85073477172Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Urban and Environmental Engineeringinfo:eu-repo/semantics/openAccess2024-06-18T15:01:27Zoai:repositorio.unesp.br:11449/199511Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:07:45.623691Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
TSRS - A new approach for traffic sign recognition using the sift algorithm |
title |
TSRS - A new approach for traffic sign recognition using the sift algorithm |
spellingShingle |
TSRS - A new approach for traffic sign recognition using the sift algorithm TSRS - A new approach for traffic sign recognition using the sift algorithm Silva, Francisco A. Character recognition RANSAC SIFT Traffic sign recognition Silva, Francisco A. Character recognition RANSAC SIFT Traffic sign recognition |
title_short |
TSRS - A new approach for traffic sign recognition using the sift algorithm |
title_full |
TSRS - A new approach for traffic sign recognition using the sift algorithm |
title_fullStr |
TSRS - A new approach for traffic sign recognition using the sift algorithm TSRS - A new approach for traffic sign recognition using the sift algorithm |
title_full_unstemmed |
TSRS - A new approach for traffic sign recognition using the sift algorithm TSRS - A new approach for traffic sign recognition using the sift algorithm |
title_sort |
TSRS - A new approach for traffic sign recognition using the sift algorithm |
author |
Silva, Francisco A. |
author_facet |
Silva, Francisco A. Silva, Francisco A. Pereira, Danillo R. Silva, João F. C. [UNESP] Artero, Almir O. [UNESP] Piteri, Marco A. [UNESP] Pereira, Danillo R. Silva, João F. C. [UNESP] Artero, Almir O. [UNESP] Piteri, Marco A. [UNESP] |
author_role |
author |
author2 |
Pereira, Danillo R. Silva, João F. C. [UNESP] Artero, Almir O. [UNESP] Piteri, Marco A. [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
University of Western São Paulo (Unoeste) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Silva, Francisco A. Pereira, Danillo R. Silva, João F. C. [UNESP] Artero, Almir O. [UNESP] Piteri, Marco A. [UNESP] |
dc.subject.por.fl_str_mv |
Character recognition RANSAC SIFT Traffic sign recognition |
topic |
Character recognition RANSAC SIFT Traffic sign recognition |
description |
This paper proposes a new approach for traffic sign recognition using images captured by a low-cost mapping system. The proposed approach applies the SIFT algorithm to extract keypoint features that are used to evaluate the correspondences between a road image containing one or more plates and the images of traffic signs (templates). The BBF algorithm was used to efficiently evaluate the correspondence between the SIFT features. Finally, we propose a new algorithm to filter only the pairs of keypoints (image-template) that are compatible as well as the orientation and positioning. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 2020-12-12T01:41:54Z 2020-12-12T01:41:54Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.4090/juee.2019.v13n1.059068 Journal of Urban and Environmental Engineering, v. 13, n. 1, p. 59-68, 2019. 1982-3932 http://hdl.handle.net/11449/199511 10.4090/juee.2019.v13n1.059068 2-s2.0-85073477172 |
url |
http://dx.doi.org/10.4090/juee.2019.v13n1.059068 http://hdl.handle.net/11449/199511 |
identifier_str_mv |
Journal of Urban and Environmental Engineering, v. 13, n. 1, p. 59-68, 2019. 1982-3932 10.4090/juee.2019.v13n1.059068 2-s2.0-85073477172 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Journal of Urban and Environmental Engineering |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
59-68 |
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_ |
1822182378945118208 |
dc.identifier.doi.none.fl_str_mv |
10.4090/juee.2019.v13n1.059068 |