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Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-13728-0_16
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dc.titleReal scene sign recognition
dc.contributor.authorLi, L.
dc.contributor.authorTan, C.L.
dc.date.accessioned2013-07-04T08:34:08Z
dc.date.available2013-07-04T08:34:08Z
dc.date.issued2010
dc.identifier.citationLi, L.,Tan, C.L. (2010). Real scene sign recognition. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6020 LNCS : 175-186. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-13728-0_16" target="_blank">https://doi.org/10.1007/978-3-642-13728-0_16</a>
dc.identifier.isbn364213727X
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41719
dc.description.abstractA common problem encountered in recognizing signs in real-scene images is the perspective deformation. In this paper, we employ a descriptor named Cross Ratio Spectrum for recognizing real scene signs. Particularly, this method will be applied in two different ways: recognizing a multi-component sign as an whole entity or recognizing individual components separately. For the second strategy, a graph matching is used to finally decide the identify of the query sign. © 2010 Springer-Verlag.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-13728-0_16
dc.sourceScopus
dc.subjectGraphics Recognition
dc.subjectPerspective Deformation
dc.subjectReal Scene Recognition
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1007/978-3-642-13728-0_16
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume6020 LNCS
dc.description.page175-186
dc.identifier.isiutNOT_IN_WOS
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