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A Hybrid Handwritten Chinese Address Recognition Approach

  • Kaizhu Huang
  • Jun Sun
  • Yoshinobu Hotta
  • Katsuhito Fujimoto
  • Satoshi Naoi
  • Chong Long
  • Li Zhuang
  • Xiaoyan Zhu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4233)

Abstract

Handwritten Chinese Address Recognition describes a difficult yet important pattern recognition task. There are three difficulties in this problem: (1) Handwritten address is often of free styles and of high variations, resulting in inevitable segmentation errors. (2) The number of Chinese characters is large, leading low recognition rate for single Chinese characters. (3) Chinese address is usually irregular, i.e., different persons may write the same address in different formats. In this paper, we propose a comprehensive and hybrid approach for solving all these three difficulties. Aiming to solve (1) and (2), we adopt an enhanced holistic scheme to recognize the whole image of words (defined as a place name) instead of that of single characters. This facilitates the usage of address knowledge and avoids the difficult single character segmentation problem as well. In order to attack (3), we propose a hybrid approach that combines the word-based language model and the holistic word matching scheme. Therefore, it can deal with various irregular address. We provide theoretical justifications, outline the detailed steps, and perform a series of experiments. The experimental results on various real address demonstrate the advantages of our novel approach.

Keywords

Word Recognition Chinese Character Edit Distance Recognition Result Word Image 
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

  • Kaizhu Huang
    • 1
  • Jun Sun
    • 1
  • Yoshinobu Hotta
    • 2
  • Katsuhito Fujimoto
    • 2
  • Satoshi Naoi
    • 2
  • Chong Long
    • 3
  • Li Zhuang
    • 3
  • Xiaoyan Zhu
    • 3
  1. 1.Information Technology LabFujitsu R&D Center LtdBeijingChina
  2. 2.Fujitsu Laboratories LtdKawasakiJapan
  3. 3.Dept. of Computer Science and TechnologyTsinghua UniversityBeijingChina

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