• DocumentCode
    3324700
  • Title

    A simple estimation the number of classes in satellite imagery

  • Author

    Koonsanit, Kitti ; Jaruskulchai, Chuleerat

  • Author_Institution
    Dept. of Comput. Sci., Kasetsart Univ., Bangkok, Thailand
  • fYear
    2012
  • fDate
    12-13 Jan. 2012
  • Firstpage
    124
  • Lastpage
    128
  • Abstract
    Clustering is a popular tool for exploratory data analysis, such as K-means and Fuzzy C-mean. A simple estimation the number of classes for segmented areas (K) in satellite imagery application is often needed in advance as an input parameter to the K-means algorithm. In this paper, a method has been developed to estimate the number of classes for segmented areas in satellite imagery clustering application using an image processing technique based on the co-occurrence matrix technique. The proposed method was tested using data from known the number of classes with satellite imagery. The results from the tests confirm the effectiveness of the proposed method in finding the estimation the number of classes and compared with ground truth data.
  • Keywords
    image segmentation; matrix algebra; pattern clustering; K-means; co-occurrence matrix; exploratory data analysis; fuzzy C-mean; image processing; satellite imagery application; satellite imagery clustering; segmented areas; simple estimation; Clustering algorithms; Color; Educational institutions; Estimation; Image segmentation; Pattern recognition; Satellites; Segmentation; clustering; satellite image; the number of classes; the number of clusters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ICT and Knowledge Engineering (ICT & Knowledge Engineering), 2011 9th International Conference on
  • Conference_Location
    Bangkok
  • Print_ISBN
    978-1-4577-2161-8
  • Type

    conf

  • DOI
    10.1109/ICTKE.2012.6152390
  • Filename
    6152390