• DocumentCode
    498950
  • Title

    Fuzzy threshold method for off-line Chinese handwritten character segmentation

  • Author

    Yang, Fang ; Si, Jian-hui ; Liu, Yong-hong ; Tian, Xue-dong

  • Author_Institution
    Coll. of Math. & Comput. Sci., Hebei Univ., Baoding, China
  • Volume
    2
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    679
  • Lastpage
    682
  • Abstract
    Off-line Chinese handwritten character segmentation usually includes the coarse and fine steps. In order to identify which regions that gotten through the coarse step should be merged or segmented again, a threshold is usually adopted. In this paper, a fuzzy threshold method is presented to adapt for the variety of unconstrained writing styles. First, the coarse segmentation region´s distribution is gotten by taking statistics with its width and height. Second, the region membership values for broken, isolated and touching character are gotten by the fuzzy functions, and then the region class is determined by the max membership value. Last, the fine segmentation step is instructed by the fuzzy threshold and feedbacks from recognizer. Experiments are performed and the results show that the fuzzy threshold method is quite simple and effective.
  • Keywords
    fuzzy set theory; handwritten character recognition; image segmentation; statistical analysis; coarse segmentation region distribution; fuzzy threshold method; offline Chinese handwritten character segmentation; region membership value; statistical analysis; Character recognition; Computer science; Cybernetics; Educational institutions; Feedback; Handwriting recognition; Image segmentation; Machine learning; Mathematics; Statistical distributions; Character segmentation; Fuzzy; Handwritten Chinese character; Off-line; Threshold;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212361
  • Filename
    5212361