• DocumentCode
    3316919
  • Title

    Fast Handwritten Chinese Characters Segmentation Algorithm Based on Active Contour Model

  • Author

    Zhu Lei ; Yang Jing

  • Author_Institution
    Coll. of Autom., Chongqing Univ., Chongqing, China
  • fYear
    2010
  • fDate
    23-25 July 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The classical C-V algorithm has the shortage about multi-iterative operations and the computational time is too long to segment the large size image. On the base of analysis upon the relationship between the image size and the number of iterations and time to get the right result, the article proposes a fast image segmentation algorithm based on local C-V active contour model which are based on threshold segmentation and the connected component labeling. In the first step, a coarse segmentation is obtained by using the OTSU method, then label and cut the image with the fast non-recursion pixel marking algorithm of connected domains. The segmentation is used as an initial solution in the C-V model. The analysis and experimental results indicate that the improved C-V algorithm can get the right result quickly compared with classical C-V algorithm. It is fast and effective to segment the large size image which has most profound contour details.
  • Keywords
    handwritten character recognition; image resolution; image segmentation; iterative methods; OTSU method; active contour model; classical C-V algorithm; connected component labeling; fast handwritten Chinese characters segmentation algorithm; multiiterative operations; nonrecursion pixel marking algorithm; threshold segmentation; Active contours; Algorithm design and analysis; Capacitance-voltage characteristics; Character recognition; Computer vision; Image analysis; Image edge detection; Image segmentation; Partial response channels; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Electronic Commerce (IEEC), 2010 2nd International Symposium on
  • Conference_Location
    Ternopil
  • Print_ISBN
    978-1-4244-6972-7
  • Electronic_ISBN
    978-1-4244-6974-1
  • Type

    conf

  • DOI
    10.1109/IEEC.2010.5533257
  • Filename
    5533257