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Data compression on multifont Chinese character patterns.

M K Tsay1, C H Kuo, R H Ju

  • 1Inst. of Comput. Sci. and Electron. Eng., Nat. Central Univ., Chung-Li.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1994
PubMed
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This study introduces a new algorithm for digital Chinese character compression. It achieves significant coding efficiency improvements, up to 32.17%, by effectively capturing data redundancies using a 2-D parsing tree model.

Area of Science:

  • Computer Science
  • Information Theory
  • Digital Image Processing

Background:

  • Digital Chinese character patterns present unique challenges for noiseless data compression.
  • Existing compression methods may not fully exploit the inherent redundancies in character data.

Purpose of the Study:

  • To develop an effective modeling and coding strategy for digital Chinese character patterns.
  • To enhance the efficiency of noiseless compression for Chinese character datasets.

Main Methods:

  • A novel redundancy-gathering algorithm is proposed, utilizing a 2-D parsing tree structure.
  • Nodes in the parsing tree are ranked based on the maximum redundancy gathered.
  • The algorithm's performance is evaluated using arithmetic coding for digital Chinese character patterns.

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Main Results:

  • The proposed modeling approach achieves high performance with a minimal number of nodes.
  • Significant improvements in coding efficiency were observed across five different Chinese fonts.
  • Efficiency gains ranged from 15.90% to 32.17% compared to traditional compression methods at similar complexity.

Conclusions:

  • The developed redundancy-gathering algorithm and 2-D parsing tree model offer a superior approach for Chinese character compression.
  • This method effectively captures data redundancies, leading to substantial improvements in compression ratios.