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Oriented Local Binary Patterns for Writer Identification
2013
IEEE International Conference on Document Analysis and Recognition
In this paper we present an oriented texture feature set and apply it to the problem of offline writer identification. Our feature set is based on local binary patterns (LBP) which were broadly used for face recognition in the past. These features are inherently texture features. Thus, we approach the writer identification problem as an oriented texture recognition task and obtain remarkable results comparable to the state of the art. Our experiments were conducted on the ICDAR 2011 and ICHFR
dblp:conf/icdar/NicolaouLI13
fatcat:xv6ibdadmrgqphzh3pc4tadwom