Classification of handprinted Chinese characters using nonlinear normalization and correlation methods

@article{Tsukumo1988ClassificationOH,
  title={Classification of handprinted Chinese characters using nonlinear normalization and correlation methods},
  author={Jun Tsukumo and Haruhiko Tanaka},
  journal={[1988 Proceedings] 9th International Conference on Pattern Recognition},
  year={1988},
  pages={168-171 vol.1}
}
A description is given of the classification of handprinted Chinese characters, using correlation methods for fast classification and a nonlinear normalization based on uniform relocation of the strokes used to form the character. Experimental results for handprinted Chinese character classification are presented. High classification capability, at 97.36% for the recognition rate and 99.44% for the rough classification was achieved for a large data set (ETL8), which includes 881 handprinted… CONTINUE READING

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Key Quantitative Results

  • High classification capability, at 97.36% for the recognition rate and 99.44% for the rough classification was achieved for a large data set (ETL8), which includes 881 handprinted Chinese characters and 160 character patterns per character.

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