• DocumentCode
    2457826
  • Title

    An Image Segmentation Method Based on Improved Watershed Algorithm

  • Author

    Zhang, Xiaoyan ; Shan, Yong ; Wei, Wei ; Zhu, Zijian

  • Author_Institution
    Dept. of Network Eng., Air Force Eng. Univ., Xi´´an, China
  • fYear
    2010
  • fDate
    17-19 Dec. 2010
  • Firstpage
    258
  • Lastpage
    261
  • Abstract
    Traditional watershed segmentation is sensitive to noise and can leads to serious over-segmentation. In order to overcome the shortcomings of traditional watershed segmentation, this paper presented an improved watershed image segmentation method. Firstly, the morphological opening/closing reconstruction filter is applied to remove the image noise. Secondly, multi-scale structure elements are used to calculate morphological gradient. Furthermore, the morphological gradient is modified by viscous morphological operators which can remove the most irregular local minimums. After the standard watershed transform, the region merging method based on neighbor regions edge value is employed to improve the segmentation result. Experiments show that this method can not only effectively avoid the over-segmentation of watershed, but also preserve the positions of regional contours.
  • Keywords
    edge detection; image denoising; image segmentation; transforms; image denoise; image segmentation; morphological gradient; region merging method; regional contours; standard watershed transform; viscous morphological operators; Algorithm design and analysis; Image edge detection; Image reconstruction; Image segmentation; Merging; Noise; Pixel; gradient modification; opening/closing reconstruction filter; viscous morphological operator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational and Information Sciences (ICCIS), 2010 International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-8814-8
  • Electronic_ISBN
    978-0-7695-4270-6
  • Type

    conf

  • DOI
    10.1109/ICCIS.2010.69
  • Filename
    5709051