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Optical Font Recognition of Chinese Characters Based on Texture Features

  • Ming-hu Ha
  • Xue-dong Tian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)

Abstract

Font recognition is a fundamental issue in the identification, analysis and reconstruction of documents. In this paper, a new method of optical font recognition is proposed which could recognize the font of every Chinese character. It employs a statistical method based on global texture analysis to recognize a predominant font, and uses a traditional recognizer of a single font to identify the font of a single character by the guidance of an obtained predominant font. It consists of three steps. First, the guiding fonts are acquired based on Gabor features. Then a font recognizer is run to identify the font of the characters one by one. Finally, a post-processing is fulfilled according to the layout knowledge to correct the errors of font recognition. Experiments are carried out and the results show that this method is of immense practical and theoretical value.

Keywords

Texture Feature Chinese Character Gabor Filter Gabor Feature Text Block 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ming-hu Ha
    • 1
  • Xue-dong Tian
    • 1
  1. 1.College of Physics Science and TechnologyHebei UniversityBaodingChina

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