• DocumentCode
    2058337
  • Title

    Feature tree clustering for image segmentation

  • Author

    Inoue, Suguru ; Hagiwara, Masafumi

  • Author_Institution
    Fac. of Sci. & Technol., Keio Univ., Kanagawa, Japan
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    2022
  • Abstract
    A new image segmentation method using a feature tree is proposed in this paper. The feature tree reflects the feature of an image. The proposed method is composed of two processes: (I) learning process and (II) clustering process. In the learning process, many efficient feature trees are made that construct an integrated tree. The integrated tree is used to segment images in the clustering process. Dividing an image is kept on from global point to local point. So, the proposed method can divide images considering not only the local property but also the global property. We applied the proposed method to some images, and obtained good results
  • Keywords
    image segmentation; tree data structures; clustering process; feature tree clustering; global property; image segmentation; integrated tree; learning process; local property; Computer networks; Computer science; Computer vision; Image analysis; Image coding; Image recognition; Image segmentation; Merging; Remote sensing; Tree data structures;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2001 IEEE International Conference on
  • Conference_Location
    Tucson, AZ
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7087-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2001.973727
  • Filename
    973727