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|Title:||Real scene sign recognition||Authors:||Li, L.
Real Scene Recognition
|Issue Date:||2010||Citation:||Li, 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. https://doi.org/10.1007/978-3-642-13728-0_16||Abstract:||A 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.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/41719||ISBN:||364213727X||ISSN:||03029743||DOI:||10.1007/978-3-642-13728-0_16|
|Appears in Collections:||Staff Publications|
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