Journal of South China University of Technology (Natural Science Edition) ›› 2010, Vol. 38 ›› Issue (10): 74-78.doi: 10.3969/j.issn.1000-565X.2010.10.014

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Character Segmentation of Offline Unconstrained Handwritten Chinese Text Lines

Li Nan-xi  Jin Lian-wen   

  1. School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2009-12-29 Revised:2010-03-03 Online:2010-10-25 Published:2010-10-25
  • Contact: 李南希（1981-），女，博士生，主要从事手写文字处理、图像处理和模式识别研究． E-mail:pumpkinlnx@gmail．com
  • About author:李南希（1981-），女，博士生，主要从事手写文字处理、图像处理和模式识别研究．
  • Supported by:

    NSFC-广东省自然科学联合基金资助项目（U0735004）; 国家自然科学基金资助项目（60772116）; 广东省自然科学基金重点资助项目（07118074）

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Abstract:

Proposed in this paper is a novel method of character segmentation for offline unconstrained handwritten Chinese text lines.In this method,first,a series of curved candidate segmentation paths are generated via a pre-segmentation algorithm.Then,the recognition information of isolated characters and the geometric information of text lines are integrated by using two modified quadratic discriminant functions,from which the confidence of the segmentation hypothesis is obtained.Moreover,the optimal segmentation hypothesis is searched by employing a dynamic programming algorithm.Finally,the proposed method is tested using 383 text lines in the HIT-MW database without the help of any language models.The segmentation accuracy reaches 89.70%,which means that the proposed method is effective.

Key words: character recognition, Chinese character segmentation, pre-segmentation, confidence, dynamic programming