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On-line Chinese character recognition with attributed relational graph matching

  • Jianzhuang Liu
  • W. K. Cham
  • Michael M. Y. Chang
Session IA1c — Document Processing & Character Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1024)

Abstract

A structural method for on-line recognition of Chinese characters is proposed, which is stroke order free and allows variations in stroke type and stroke number. Both input characters and the model characters are represented with complete attributed relational graphs (ARGs). An optimal matching measure between two ARGs is defined. Classification of an input character can be implemented by inexactly matching its ARG against every ARG of the model base. The matching procedure is formulated as a search problem of finding the minimum cost path in a state space tree, using the A* algorithm. In order to speed up the search of the A*, besides a heuristic estimate, a novel strategy that utilizes the geometric position information of strokes of Chinese characters to prune the tree is employed. The efficience of our method is demonstrated by the promising experimental results.

Keywords

Goal Node Chinese Character Input Character Stroke Type Minimum Cost Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Jianzhuang Liu
    • 1
  • W. K. Cham
    • 1
  • Michael M. Y. Chang
    • 2
  1. 1.Department of Electronic EngineeringThe Chinese University of Hong KongHong Kong
  2. 2.Department of Information EngineeringThe Chinese University of Hong KongHong Kong

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