• DocumentCode
    2794402
  • Title

    Application of Fuzzy Enhancement Algorithm and KSW Entropy Algorithm in Segmentation of Pre-welding Seam Image

  • Author

    Liu, Xiwen ; Wang, Guorong ; Shi, Yonghua

  • Author_Institution
    Dept. of Mech. Eng., South China Univ. of Technol., Guangzhou
  • Volume
    1
  • fYear
    2006
  • fDate
    16-18 Oct. 2006
  • Firstpage
    260
  • Lastpage
    263
  • Abstract
    Fuzzy enhancement algorithm and KSW entropy algorithm are proposed for pre-welding seam image segmentation. Before automatic welding, the welding seam image is often segmented so that it can be recognized by robot. KSW entropy algorithm is an effective way for segmentation. Image enhancement is often applied before segmentation in order to get better result. As the pre-welding seam image is not uniform, the effect is not ideal after applying regular enhancement algorithm and KSW entropy algorithms to it. Fuzzy enhancement algorithm can eliminate the noises and preserve the details of the image intelligently. The image dividing point has close relation with the result of fuzzy enhancement algorithm. Self adapting algorithm about how to get the proper image dividing point is discussed. When fuzzy enhancement algorithm and KSW entropy segmentation algorithm are used to pre-welding seam image, the experiment results prove that the best effect can be got and little time will be cost
  • Keywords
    entropy; fuzzy set theory; image denoising; image enhancement; image segmentation; robotic welding; KSW entropy; automatic welding; fuzzy enhancement; image denoising; image enhancement; prewelding seam image segmentation; welding robots; Entropy; Histograms; Image edge detection; Image enhancement; Image processing; Image segmentation; Mechanical engineering; Robot vision systems; Robotics and automation; Welding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    0-7695-2528-8
  • Type

    conf

  • DOI
    10.1109/ISDA.2006.101
  • Filename
    4021446