• DocumentCode
    3562634
  • Title

    Local binary pattern texture feature for satellite imagery classification

  • Author

    Vigneshl, T. ; Thyagharajan, K.K.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., S.A. Eng. Coll., Chennai, India
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The Texture Feature Extraction (TFE) plays an important role in satellite image processing application. This paper proposes a novel method for Satellite Imagery Classification. Our proposed method is a combination of Local Binary Pattern (LBP) and Fuzzy c-means classification algorithm. Local Binary Pattern is calculated by thresholding a 3 × 3 neighborhood of each pixel by the center pixel value. During the Feature Extraction Phase, Local Binary Pattern extracts the important characteristics from the satellite images. Fuzzy c-means algorithm classifying the images into different classes. This is a very challenging task in texture feature extraction being used in satellite images.
  • Keywords
    image processing; remote sensing; Feature Extraction Phase; Fuzzy c-means classification algorithm; Texture Features Extraction; center pixel value; local binary pattern; satellite image processing application; satellite imagery classification; Accuracy; Classification algorithms; Clustering algorithms; Educational institutions; Feature extraction; Remote sensing; Satellites; Classification; Feature extraction; Fuzzy c-means; Local Binary pattern; Satellite image processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Science Engineering and Management Research (ICSEMR), 2014 International Conference on
  • Print_ISBN
    978-1-4799-7614-0
  • Type

    conf

  • DOI
    10.1109/ICSEMR.2014.7043591
  • Filename
    7043591