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dc.contributor.authorLi, Y.-
dc.contributor.authorShen, C.-
dc.contributor.authorJia, W.-
dc.contributor.authorVan Den Hengel, A.-
dc.identifier.citation2013 IEEE International Conference on Image Processing, ICIP 2013 Proceedings, Melbourne, Vic., Australia, 15-18 September 2013: pp.2264-2268-
dc.description.abstractFinding text in natural images has been a challenging task in vision. At the core of state-of-the-art scene text detection algorithms are a set of text-specific features within extracted regions. In this paper, we attempt to solve this problem from a different prospective. We show that characters and non-character interferences are separable by leveraging the surrounding context. Surrounding context, in our work, is composed of two components which are computed in an information-theoretic fashion. Minimization of an energy cost function yields a binary label for each region, which indicates the category it belongs to. The proposed algorithm is fast, discriminative and tolerant to character variations and involves minimal parameter tuning.-
dc.description.statementofresponsibilityYao Li, Chunhua Shen, Wenjing Jia, Anton van den Hengel-
dc.relation.ispartofseriesIEEE International Conference on Image Processing ICIP-
dc.rights© 2013 IEEE-
dc.subjectSurrounding context, energy minimization, scene text detection-
dc.titleLeveraging surrounding context for scene text detection-
dc.typeConference paper-
dc.contributor.conferenceInternational Conference on Image Processing (20th : 2013 : Melbourne, Australia)-
dc.identifier.orcidVan Den Hengel, A. [0000-0003-3027-8364]-
Appears in Collections:Aurora harvest
Computer Science publications

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