• DocumentCode
    1885662
  • Title

    Contourlet Retrieval System Using Absolute Mean and Kurtosis Features

  • Author

    Chen, Xin-Wu ; Liu, Yu-Xi

  • Author_Institution
    Coll. of Phys. & Electron., Xinyang Normal Univ., Xinyang, China
  • fYear
    2010
  • fDate
    25-26 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    To improve the retrieval rate of contourlet transform retrieval system,a new contourlet retrieval system was proposed.The feature vectors were constructed by cascading the absolute mean energy and kurtosis of each sub-band contourlet coefficients and the similarity measure used here is Canberra distance. Experimental results on 109 brodatz texture images show that using the features cascaded by absolute mean and kurtosis can lead to a higher retrieval rate than the combination of standard deviation and absolute mean which is most commonly used today under same dimension of feature vectors.
  • Keywords
    image retrieval; image texture; transforms; Canberra distance; absolute mean energy; contourlet transform retrieval system; feature vectors; kurtosis features; standard deviation; Energy measurement; Feature extraction; Image retrieval; Manganese; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2156-7379
  • Print_ISBN
    978-1-4244-7939-9
  • Electronic_ISBN
    2156-7379
  • Type

    conf

  • DOI
    10.1109/ICIECS.2010.5677689
  • Filename
    5677689