• DocumentCode
    2430134
  • Title

    Image Clustering Using Mean Shift Algorithm

  • Author

    Bo, Shukui ; Jing, Yongju

  • Author_Institution
    Dept. of Comput. Sci. & Applic., Zhengzhou Inst. of Aeronaut. Ind. Manage., Zhengzhou, China
  • fYear
    2012
  • fDate
    3-5 Nov. 2012
  • Firstpage
    327
  • Lastpage
    330
  • Abstract
    Clustering is an important technique of image analysis. Mean shift based clustering is a nonparametric method and can find arbitrary shape clusters in the feature space of an image. In this paper, we present a re-clustering technique based on the mean shift algorithm. The proposed method consists of two steps. First step divides the original image into homogenous image segments. Second step clusters the image segments to obtain the result of image clustering. An experiment is carried out on a remote sensing image. In the experiment, the method is compared with the traditional mean shift based image clustering. The results show that this method is better than the traditional method in classification accuracy.
  • Keywords
    image classification; image segmentation; pattern clustering; remote sensing; arbitrary shape clusters; homogenous image segments; image analysis; image clustering; image feature space; mean shift algorithm; mean shift based clustering; nonparametric method; re-clustering technique; remote sensing image; Accuracy; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Image segmentation; Remote sensing; Vectors; clustering; mean shift; remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Communication Networks (CICN), 2012 Fourth International Conference on
  • Conference_Location
    Mathura
  • Print_ISBN
    978-1-4673-2981-1
  • Type

    conf

  • DOI
    10.1109/CICN.2012.128
  • Filename
    6375127