• DocumentCode
    1938323
  • Title

    Alternative Noise Clustering Algorithm

  • Author

    Wu, Xiao-Hong ; Zhou, Jian-Jiang

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Jiangsu Univ.
  • Volume
    3
  • fYear
    2006
  • fDate
    16-20 2006
  • Abstract
    Based on a new distance, a novel noise-resistant fuzzy clustering algorithm called alternative noise clustering (ANC) algorithm is proposed. ANC is an extension of the noise clustering (NC) algorithm proposed by Dave. By replacing the Euclidean distance used in the objective function of NC algorithm, a new distance (non-Euclidean distance) is introduced in NC algorithm. Based on robust statistical point of view and influence function, the non-Euclidean distance is more robust than the Euclidean distance. So the ANC algorithm is more robust than the NC algorithm. Moreover, with the new distance ANC can deal with noises or outliers better than NC and fuzzy c-means (FCM). Performing experiments on data sets shows the better performance of the proposed algorithm
  • Keywords
    fuzzy set theory; image processing; pattern clustering; statistical analysis; alternative noise clustering algorithm; digital image processing; noise-resistant fuzzy clustering algorithm; non-Euclidean distance; Clustering algorithms; Digital images; Educational institutions; Euclidean distance; Fuzzy sets; Information science; Noise robustness; Partitioning algorithms; Prototypes; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2006 8th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9736-3
  • Electronic_ISBN
    0-7803-9736-3
  • Type

    conf

  • DOI
    10.1109/ICOSP.2006.345777
  • Filename
    4129208