Publication | Open Access
BoR: BAG-OF-RELATIONS FOR SYMBOL RETRIEVAL
25
Citations
41
References
2014
Year
EngineeringImage RetrievalBiometricsImage SearchText MiningVisual PrimitivesImage AnalysisInformation RetrievalText-to-image RetrievalPattern RecognitionComputational LinguisticsNew SchemeMachine VisionSymbol RetrievalKnowledge DiscoveryComputer ScienceSymbolic Linguistic RepresentationImage SimilarityComputer VisionSimilarity SearchContent-based Image Retrieval
In this paper, we address a new scheme for symbol retrieval based on bag-of-relations (BoRs) which are computed between extracted visual primitives (e.g. circle and corner). Our features consist of pairwise spatial relations from all possible combinations of individual visual primitives. The key characteristic of the overall process is to use topological relation information indexed in BoRs and use this for recognition. As a consequence, directional relation matching takes place only with those candidates having similar topological configurations. A comprehensive study is made by using several different well-known datasets such as GREC, FRESH and SESYD, and includes a comparison with state-of-the-art descriptors. Experiments provide interesting results on symbol spotting and other user-friendly symbol retrieval applications.
| Year | Citations | |
|---|---|---|
Page 1
Page 1