• DocumentCode
    2505862
  • Title

    Image resolution dependency of Local Texture Patterns in classification of color images

  • Author

    Suruliandi, A. ; Srinivasan, E.M. ; Ramar, K.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Manonmaniam Sundaranar Univ., Tirunelveli, India
  • fYear
    2010
  • fDate
    17-19 Dec. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, experiments have been conducted to study the significance of the dots per inch resolution of the color images in texture classification. Textural features of the image are extracted using Gray-Local Texture Patterns (GLTP) operator which is an extended version of Local Texture Patterns (LTP) texture model. Contrast being another important property of images, Color-Local Contrast Variance Patterns (CLCVP) is used to extract contrast feature. However, much important information contained in the image can be revealed by joint distributions of individual features. Hence, GLTP/CLCVP is used as a textural feature extraction technique for classification of color images. The performance of the GLTP/CLCVP operator is tested for classification of images from Outex texture database. From the experimental results, it is observed that the classification accuracy is highly dependent on the dots per inch resolution of the images.
  • Keywords
    feature extraction; image classification; image colour analysis; image resolution; image texture; CLCVP; GLTP; color image classification; color-local contrast variance pattern; gray-local texture pattern; image resolution dependency; textural feature extraction technique; Color; Feature extraction; Histograms; Image color analysis; Image resolution; Image texture; Training; Local Color Contrast Variance Patterns; Local Gray Scale Texture Patterns; Local Texture Patterns; Texture Analysis; Texture Classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    India Conference (INDICON), 2010 Annual IEEE
  • Conference_Location
    Kolkata
  • Print_ISBN
    978-1-4244-9072-1
  • Type

    conf

  • DOI
    10.1109/INDCON.2010.5712590
  • Filename
    5712590