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.
A study on the use of CDHMM for large vocabulary off-line recognition of handwritten Chinese characters
2002-01-01
327620 byte
Conference paper
Electronic Resource
English
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British Library Conference Proceedings | 2003
|Recognition of handwritten Chinese characters by elastic matching
British Library Online Contents | 1998
|