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Metasynthetic Approach For Handwritten Chinese Character Recognition

Author

Listed:
  • BAIHUA XIAO

    (AI Lab, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100080, PR China)

  • CHUNHENG WANG

    (AI Lab, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100080, PR China)

  • RUWEI DAI

    (AI Lab, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100080, PR China)

Abstract

The metasynthetic approach for solving complicated problems was proposed in 1990.1And the characteristics of metasynthetic approach can be summarized as human-machine cooperation and integration. Directed by the idea of metasynthesis, the design of two kinds of handwritten Chinese character recognition systems are given in this article. All the designs focus on incorporating human knowledge into multiple classifier combination, which is different from conventional integration. The first one is multi-stage adaptive weighted multiple classifier combination, in which a neural network for coefficient predicting is trained by supervised learning to provide weights suitable for the input pattern. And the second scheme is based on totally parallel combination, in which human intelligence and computer capabilities are combined together through multi-step supervised learning. The experimental results demonstrate substantial improvement in overall performance for handwritten Chinese character recognition with thousands of classes that must be discriminated.

Suggested Citation

  • Baihua Xiao & Chunheng Wang & Ruwei Dai, 2002. "Metasynthetic Approach For Handwritten Chinese Character Recognition," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 1(04), pages 621-633.
    • Handle: RePEc:wsi:ijitdm:v:01:y:2002:i:04:n:s0219622002000488
    DOI: 10.1142/S0219622002000488
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