• DocumentCode
    442867
  • Title

    A semi-supervised color image segmentation method

  • Author

    Qian, Yuntao ; Si, Wenwu

  • Author_Institution
    Sch. of Comput. Sci., Zhejiang Univ., Hangzhou, China
  • Volume
    2
  • fYear
    2005
  • fDate
    11-14 Sept. 2005
  • Abstract
    A new color image segmentation algorithm based on semi-supervised clustering is proposed, which integrates limited human assistance, a user indicates the relationship of some different regions in an image by mouse, to get the final accurate segmentation result which satisfies the prior segmentation constraints. The algorithm first has the image quantified and then clusters in the quantified color space with prior segmentation information. Experiment results show that the proposed algorithm is effective and has high value of utility.
  • Keywords
    image colour analysis; image segmentation; learning (artificial intelligence); human assistance; quantified color space; semisupervised clustering; semisupervised color image segmentation method; Clustering algorithms; Color; Humans; Image retrieval; Image segmentation; Layout; Machine vision; Mice; Pixel; Semisupervised learning; EM algorithm; clustering; image segmentation; semi-supervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2005. ICIP 2005. IEEE International Conference on
  • Print_ISBN
    0-7803-9134-9
  • Type

    conf

  • DOI
    10.1109/ICIP.2005.1530275
  • Filename
    1530275