• DocumentCode
    2345301
  • Title

    Spatial Multiple Criteria Fuzzy Clustering for Image Segmentation

  • Author

    Rajeswari, Mandava ; Wei, Bong Chin ; Yeow, Lee Song

  • Author_Institution
    Sch. of Comput. Sci., Univ. Sains Malaysia, Minden, Malaysia
  • fYear
    2010
  • fDate
    28-30 Sept. 2010
  • Firstpage
    305
  • Lastpage
    310
  • Abstract
    In this paper, we propose a spatial fuzzy clustering method based on multiple criteria optimization method. Our fuzzy clustering method is an enhanced version of fuzzy c-means (FCM) with consideration of multiple criteria. We initiate our multiple criteria optimization approach with two criteria in term of the features of an image: spatial information and intensity. Our spatial clustering attempts to overcome the limitation of conventional FCM. We have tested the proposed method on synthetic and coins images with added Gaussian and Salt and Pepper noises. Besides, we also experiment on real medical images (Magnetic Resonance Images (MRI)) for brain and osteosarcoma (bone tumour). The result reported was encouraging.
  • Keywords
    feature extraction; image segmentation; optimisation; pattern clustering; Gaussian noise; Pepper noise; Salt noise; brain image; coins image; fuzzy c-means method; image segmentation; intensity feature; magnetic resonance images; multiple criteria optimization method; osteosarcoma image; spatial fuzzy clustering method; spatial information feature; Image segmentation; fuzzy clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence, Modelling and Simulation (CIMSiM), 2010 Second International Conference on
  • Conference_Location
    Bali
  • Print_ISBN
    978-1-4244-8652-6
  • Electronic_ISBN
    978-0-7695-4262-1
  • Type

    conf

  • DOI
    10.1109/CIMSiM.2010.65
  • Filename
    5701861