• DocumentCode
    1863034
  • Title

    Effect of gray-level re-quantization on co-occurrence based texture analysis

  • Author

    Patel, Mehul B. ; Rodriguez, Jeffrey J. ; Gmitro, Arthur F.

  • Author_Institution
    Dept. of ECE, Univ. of Arizona, Tucson, AZ
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    585
  • Lastpage
    588
  • Abstract
    Gray-level co-occurrence matrices (GLCM) are widely used for texture analysis. The number of gray-levels used while computing GLCM is an important parameter but is often ignored. It is believed that the higher the number of gray-levels used, the better is the performance of the GLCM-based features. Contrary to this belief, we observed that using more gray levels than the actual range of pixel values in the image can give erroneous results. In this paper, we show how this occurs and discuss a way around this problem.
  • Keywords
    feature extraction; image texture; matrix algebra; GLCM-based feature; gray-level co-occurrence matrix; gray-level requantization; image pixel value; texture analysis; Algorithm design and analysis; Biomedical computing; Biomedical imaging; Computational efficiency; Fluorescence; Image analysis; Image texture analysis; Lighting; Pixel; Quantization; Gray-level co-occurrence matrix; histogram; re-quantization; texture analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-1765-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2008.4711822
  • Filename
    4711822