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)


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.


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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  1. 1.
    C. C. Tappet, C. Y. Suen, and T. Wakahara, The state of the art in on-line handwriting recognition, IEEE Trans. PAMI 12, 1990, pp. 787–808Google Scholar
  2. 2.
    V. K. Govindan and A. P. Shivaprasad, Character recognition — a review, Pattern Recognition 23, 1990, pp. 671–683Google Scholar
  3. 3.
    W. H. Tsai and K. S. Fu, Error-correcting isomorphisms of attributed relational graphs for pattern analysis, IEEE Trans. SMC 9, 1979, pp. 757–768Google Scholar
  4. 4.
    R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis, Wiley-Interscience, New York, 1973Google Scholar
  5. 5.
    F. S. Hillier and G. J. Lieberman, Introduction to Operations Research, McGraw-Hill, New York, 1990Google Scholar
  6. 6.
    C. Thornton and B. D. Boulay, Artificial Intelligence through Search, Kluwer Academic Publishers, The Netherlands, 1992Google Scholar
  7. 7.
    J. Pearl, Heuristics; intelligent search strategies for computer problem solving, Addison-Wesley, Reading, MA, 1984Google Scholar
  8. 8.
    A. K. C. Wong, M. You, and S. C. Chan, An algorithm for graph optimal monomorphism, IEEE Trans. SMC 20, 1990, pp. 628–636Google Scholar

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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