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Axial Representation of Character by Using Wavelet Transform

  • Xinge You
  • Bin Fang
  • Yuan Yan Tang
  • Luoqing Li
  • Dan Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3614)

Abstract

Axial representation plays a significant role in character recognition. The strokes of a character may consist of two regions, i.e. singular and regular regions. Therefore, a method to extract the central axis of a character requires two different processes to compute the axis in theses two different regions. The major problem of most traditional algorithms is that the extracted central axis in the singular region may be distorted by artifacts and branches. To overcome this problem, the wavelet-based amendment processing technique is developed to link the primary axis, so that the central axis in the singular region can be produced. Combining with our previously developed method for computing the primary axis in the regular region, we develop a novel scheme of extracting the central axis of character based on the wavelet transform (WT). Experimental results show that the final axis obtained from the proposed scheme closely resembles the human perceptions. It is applicable to both binary image and gray-level image as well. The axis representation is robust against noise.

Keywords

Characteristic Point Wavelet Trans Corner Point Wavelet Function Modulus Maximum 
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 2005

Authors and Affiliations

  • Xinge You
    • 1
    • 2
  • Bin Fang
    • 2
    • 3
  • Yuan Yan Tang
    • 1
    • 2
  • Luoqing Li
    • 1
  • Dan Zhang
    • 1
  1. 1.Faculty of Mathematics and Computer ScienceHubei UniversityP.R. China
  2. 2.Department of Computer ScienceHong Kong Baptist University 
  3. 3.Chongqing University 

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