dc.contributorUniversity of Western São Paulo (Unoeste)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-12T01:41:54Z
dc.date.accessioned2022-12-19T20:53:36Z
dc.date.available2020-12-12T01:41:54Z
dc.date.available2022-12-19T20:53:36Z
dc.date.created2020-12-12T01:41:54Z
dc.date.issued2019-01-01
dc.identifierJournal of Urban and Environmental Engineering, v. 13, n. 1, p. 59-68, 2019.
dc.identifier1982-3932
dc.identifierhttp://hdl.handle.net/11449/199511
dc.identifier10.4090/juee.2019.v13n1.059068
dc.identifier2-s2.0-85073477172
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5380145
dc.description.abstractThis 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.
dc.languageeng
dc.relationJournal of Urban and Environmental Engineering
dc.sourceScopus
dc.subjectCharacter recognition
dc.subjectRANSAC
dc.subjectSIFT
dc.subjectTraffic sign recognition
dc.titleTSRS - A new approach for traffic sign recognition using the sift algorithm
dc.typeArtículos de revistas


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