Publication: Oriented Local Binary Patterns for Writer Identification


Authors: Anguelos Nicolaou, Marcus Liwicki, Rolf Ingolf


Published in: AFHA 2013


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Abstract:
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 2012 writer identification contest datasets. On these datasets we investigate the strengths of our approach as well its limitations.


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bibtex entry :
 @article{nicolaouoriented,
title={Oriented Local Binary Patterns for Writer Identification},
author={Nicolaou, Anguelos and Liwicki, Marcus and Ingold, Rolf},
journal={ONLINE PROCEEDINGS}
}


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