Optical Chinese character recognition for low-quality document images

Tzren Ru Chou, Fu Chang

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

3 Citations (Scopus)

Abstract

In this article, we propose a new matching method for machine recognition of Chinese characters that are extracted from low-quality document images. This method employs a deformation representation, called character deformation model, to guide the detailed matching between templates and unknown characters. Experimental results show that the proposed method is very effective to recognize deformed characters extracted from low-resolution images or Xerox-copy documents. A recognition rate of 95.7% is achieved for 200 dpi document images, and the accumulated recognition rate of the first 3 candidates is higher than 99.8%. Moreover, even for the 100 dpi document images, the third accumulated recognition rate is still above 91%.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Editors Anon
PublisherIEEE
Pages608-611
Number of pages4
Volume2
Publication statusPublished - 1997
Externally publishedYes
EventProceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2) - Ulm, Ger
Duration: 1997 Aug 181997 Aug 20

Other

OtherProceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2)
CityUlm, Ger
Period97/8/1897/8/20

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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