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Hybrid statistical-structural on-line Chinese character recognition with fuzzy inference system

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Hybrid statistical-structural on-line Chinese character recognition with fuzzy inference system
In this paper, we propose an original hybrid statistical-structural method for on-line Chinese character recognition. We model characters thanks to fuzzy inference rules combining morphological and contextual information formalized in a homogeneous way. For that purpose, we define a set of primitives modeling all the stroke classes that can be found in handwritten Chinese characters. Thus, each analyzed stroke can be classified as primitive without any segmentation process. Inference rules are built from the coupling of a priori information about the primitives constituting the characters and automatic modeling of their relative positioning. The fuzzy inference system aggregates these rules for decision making. First experiments validate this method with a recognition rate of 97.5% on a subset of Chinese characters.
Éric Anquetil, Adrien Delaye, Sébast
Added 05 Nov 2009
Updated 05 Nov 2009
Type Conference
Year 2008
Where ICPR
Authors Éric Anquetil, Adrien Delaye, Sébastien Macé
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