• DocumentCode
    510236
  • Title

    Some Remarks on FCMLS and its Application to Natural Fruit Image Segmentation

  • Author

    Xie, Zhenping

  • Author_Institution
    Sch. of Digital Media, Jiangnan Univ., Wuxi, China
  • Volume
    3
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    173
  • Lastpage
    177
  • Abstract
    It is well known that fuzzy clustering and level set are two important tools for image segmentation. The former focuses on analyzing the statistical characteristics of image features, while the latter aims to acquire the good geometrical continuity of segmentation boundaries. Obviously, two kinds of methods may complement each other. Inspired by this idea, a new level set model integrated with fuzzy c-means (FCM) clustering FCMLS has been presented in our previous studies. Compared with FCM and original level set methods, some remarkable characteristics and better performance have been demonstrated. In this paper, some further works are reported, mainly including the detailed analysis on the convergence of FCMLS, multiregional FCMLS, and the application to natural fruit image segmentation. Corresponding research results assert that FCMLS has good stable convergence, ant is very valuable to natural fruit image segmentation.
  • Keywords
    fuzzy set theory; image segmentation; pattern clustering; fuzzy c-means clustering; level set model; natural fruit image segmentation; Artificial intelligence; Computational intelligence; Convergence; Data mining; Fuzzy sets; Image analysis; Image color analysis; Image segmentation; Image texture analysis; Level set; FCMLS; Fuzzy clustering; level set; natural fruit image segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.110
  • Filename
    5376590