Automatic Detection and Recognition of Text-Based Traffic Signs from Images

Detalhes bibliográficos
Autor(a) principal: Oliveira, G.
Data de Publicação: 2018
Outros Autores: Silva, F., Pereira, D., Almeida, L., Artero, A. [UNESP], Bonora, A., Albuquerque, V. de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/TLA.2018.8804261
http://hdl.handle.net/11449/184663
Resumo: Detection and recognition of texts in traffic signs has been widely studied and with the advance in image capture technology has helped to improve or to create new methods to achieve this issue. In this work, we presented a method for detection, segmentation and recognition of text-based traffic signs from images analyzing and processing techniques. The results show that the computational cost and accuracy rate considering the proposed approach are acceptable to real time applications, with an execution time under 0.5 seconds, with a hit rate of 94.38% in the plate detection, 83.42% in the character segmentation and 89.23 in the digit classification.
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spelling Automatic Detection and Recognition of Text-Based Traffic Signs from ImagesTraffic signs detectionTraffic signs recognitionCharacters segmentationOCRDetection and recognition of texts in traffic signs has been widely studied and with the advance in image capture technology has helped to improve or to create new methods to achieve this issue. In this work, we presented a method for detection, segmentation and recognition of text-based traffic signs from images analyzing and processing techniques. The results show that the computational cost and accuracy rate considering the proposed approach are acceptable to real time applications, with an execution time under 0.5 seconds, with a hit rate of 94.38% in the plate detection, 83.42% in the character segmentation and 89.23 in the digit classification.Univ Oeste Paulista, Unoeste, Presidente Prudente, SP, BrazilUniv Estadual Paulista, Unesp, Presidente Prudente, SP, BrazilUniv Fortaleza, Unifor, Programa Grad Informat, Fortaleza, Ceara, BrazilUniv Estadual Paulista, Unesp, Presidente Prudente, SP, BrazilIeee-inst Electrical Electronics Engineers IncUniv Oeste PaulistaUniversidade Estadual Paulista (Unesp)Univ FortalezaOliveira, G.Silva, F.Pereira, D.Almeida, L.Artero, A. [UNESP]Bonora, A.Albuquerque, V. de2019-10-04T12:15:40Z2019-10-04T12:15:40Z2018-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article2947-2953http://dx.doi.org/10.1109/TLA.2018.8804261Ieee Latin America Transactions. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 12, p. 2947-2953, 2018.1548-0992http://hdl.handle.net/11449/18466310.1109/TLA.2018.8804261WOS:000482564600015Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIeee Latin America Transactionsinfo:eu-repo/semantics/openAccess2021-10-23T19:49:56Zoai:repositorio.unesp.br:11449/184663Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:22:31.033160Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Automatic Detection and Recognition of Text-Based Traffic Signs from Images
title Automatic Detection and Recognition of Text-Based Traffic Signs from Images
spellingShingle Automatic Detection and Recognition of Text-Based Traffic Signs from Images
Oliveira, G.
Traffic signs detection
Traffic signs recognition
Characters segmentation
OCR
title_short Automatic Detection and Recognition of Text-Based Traffic Signs from Images
title_full Automatic Detection and Recognition of Text-Based Traffic Signs from Images
title_fullStr Automatic Detection and Recognition of Text-Based Traffic Signs from Images
title_full_unstemmed Automatic Detection and Recognition of Text-Based Traffic Signs from Images
title_sort Automatic Detection and Recognition of Text-Based Traffic Signs from Images
author Oliveira, G.
author_facet Oliveira, G.
Silva, F.
Pereira, D.
Almeida, L.
Artero, A. [UNESP]
Bonora, A.
Albuquerque, V. de
author_role author
author2 Silva, F.
Pereira, D.
Almeida, L.
Artero, A. [UNESP]
Bonora, A.
Albuquerque, V. de
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Univ Oeste Paulista
Universidade Estadual Paulista (Unesp)
Univ Fortaleza
dc.contributor.author.fl_str_mv Oliveira, G.
Silva, F.
Pereira, D.
Almeida, L.
Artero, A. [UNESP]
Bonora, A.
Albuquerque, V. de
dc.subject.por.fl_str_mv Traffic signs detection
Traffic signs recognition
Characters segmentation
OCR
topic Traffic signs detection
Traffic signs recognition
Characters segmentation
OCR
description Detection and recognition of texts in traffic signs has been widely studied and with the advance in image capture technology has helped to improve or to create new methods to achieve this issue. In this work, we presented a method for detection, segmentation and recognition of text-based traffic signs from images analyzing and processing techniques. The results show that the computational cost and accuracy rate considering the proposed approach are acceptable to real time applications, with an execution time under 0.5 seconds, with a hit rate of 94.38% in the plate detection, 83.42% in the character segmentation and 89.23 in the digit classification.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-01
2019-10-04T12:15:40Z
2019-10-04T12:15:40Z
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/10.1109/TLA.2018.8804261
Ieee Latin America Transactions. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 12, p. 2947-2953, 2018.
1548-0992
http://hdl.handle.net/11449/184663
10.1109/TLA.2018.8804261
WOS:000482564600015
url http://dx.doi.org/10.1109/TLA.2018.8804261
http://hdl.handle.net/11449/184663
identifier_str_mv Ieee Latin America Transactions. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 12, p. 2947-2953, 2018.
1548-0992
10.1109/TLA.2018.8804261
WOS:000482564600015
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Ieee Latin America Transactions
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 2947-2953
dc.publisher.none.fl_str_mv Ieee-inst Electrical Electronics Engineers Inc
publisher.none.fl_str_mv Ieee-inst Electrical Electronics Engineers Inc
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_ 1808129513329000448

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