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Two Thresholding for Deriving the Bi-level Document Image

  • Yu-Kumg Chen
  • Yi-Fan Chang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4319)

Abstract

Optical character recognition occupies a very important field in digital image processing. It is used extensively in daily life. If the given image does not have a bimodal intensity histogram, it will cause segmenting mistake easily for the previous algorithms of image binarization. In order to solve this problem, a new algorithm is proposed in this paper. The proposed algorithm uses the theory of moving average on the histogram of the fuzzy image, and then derives the better histogram. Since use only one thresholding value cannot solve this problem completely, the edge information and the window processing are introduced in this paper for advanced thresholding. Thus, a more refine bi-level image is derived and it will result in the improvement of optical character recognition. Experiments are carried out for some samples with shading to demonstrate the computational advantage of the proposed method.

Keywords

Original Image Document Image Optical Character Recognition Thresholding Method Edge Information 
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

  • Yu-Kumg Chen
    • 1
  • Yi-Fan Chang
    • 1
  1. 1.Department of Electronic EngineeringHuafan UniversityTaipeiTaiwan

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