We (2002) have investigate how to use Gaussian mixture continuous-density hidden Markov models (CDHMMs) for handwritten Chinese character modeling and recognition. We have identified and developed a set of techniques that can be used to construct a practical CDHMM-based off-line recognition system for a large vocabulary of handwritten Chinese characters. We have reported elsewhere the key techniques that contribute to the high recognition accuracy. In this paper we describe how to make our recognizer compact without sacrificing too much of the recognition accuracy. We also report the results of a series of experiments that were performed to help us make a good decision when we face several design choices.


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    Title :

    A study on the use of CDHMM for large vocabulary off-line recognition of handwritten Chinese characters


    Contributors:
    Yong Ge, (author) / Qinah Huo, (author)


    Publication date :

    2002-01-01


    Size :

    327620 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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