Two-stage segmentation of unconstrained handwritten Chinese characters

Shuyan Zhao, Zheru Chi, Penfei Shi, Hong Yan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

52 Citations (Scopus)

Abstract

Correct segmentation of handwritten Chinese characters is crucial to their successful recognition. However, due to many difficulties involved, little work has been reported in this area. In this paper, a two-stage approach is presented to segment unconstrained handwritten Chinese characters. A handwritten Chinese character string is first coarsely segmented according to the background skeleton and vertical projection after a proper image preprocessing. With several geometric features, all possible segmentation paths are evaluated by using the fuzzy decision rules learned from examples. As a result, unsuitable segmentation paths are discarded. In the fine segmentation stage that follows, the strokes that may contain segmentation points are first identified. The feature points are then extracted from candidate strokes and taken as segmentation point candidates through each of which a segmentation path may be formed. The geometric features similar to the coarse segmentation stage are used and corresponding fuzzy decision rules are generated to evaluate fine segmentation paths. Experimental results on 1000 Chinese character strings from postal mail show that our approach can achieve a reasonable good overall accuracy in segmenting unconstrained handwritten Chinese characters.
Original languageEnglish
Pages (from-to)145-156
Number of pages12
JournalPattern Recognition
Volume36
Issue number1
DOIs
Publication statusPublished - 1 Jan 2003

Keywords

  • Character segmentation
  • Chinese character recognition
  • Decision trees
  • Fuzzy decision rules
  • Image preprocessing
  • Unconstrained handwritten Chinese characters

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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