Hybrid Statistical-Structural On-line Chinese Character Recognition with Fuzzy Inference SystemReport as inadecuate




Hybrid Statistical-Structural On-line Chinese Character Recognition with Fuzzy Inference System - Download this document for free, or read online. Document in PDF available to download.

1 IMADOC - Interprétation et Reconnaissance d’Images et de Documents UR1 - Université de Rennes 1, INSA Rennes - Institut National des Sciences Appliquées - Rennes, CNRS - Centre National de la Recherche Scientifique : UMR6074

Abstract : 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.





Author: Adrien Delaye - Sébastien Macé - Eric Anquetil -

Source: https://hal.archives-ouvertes.fr/



DOWNLOAD PDF




Related documents