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

Yong Ge, Qinah Huo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings - 8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002
Pages334-338
Number of pages5
DOIs
StatePublished - 2002
Externally publishedYes
Event8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002 - Ontario, ON, Canada
Duration: Aug 6 2002Aug 8 2002

Publication series

NameProceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR
ISSN (Print)1550-5235

Conference

Conference8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002
Country/TerritoryCanada
CityOntario, ON
Period8/6/028/8/02

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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