• DocumentCode
    1367496
  • Title

    Gray level thresholding in badly illuminated images

  • Author

    Parker, J.R.

  • Author_Institution
    Dept. of Comput. Sci., Calgary Univ., Alta., Canada
  • Volume
    13
  • Issue
    8
  • fYear
    1991
  • fDate
    8/1/1991 12:00:00 AM
  • Firstpage
    813
  • Lastpage
    819
  • Abstract
    The thresholding method involves first locating objects in an image by using the intensity gradient, then noting the levels that correspond to the objects in various areas of the image, and finally using these levels as initial guesses at a threshold. This method is capable of thresholding images that have been produced in the context of variable illumination. The thresholding method, called the local intensity gradient (LIG) method, was implemented in C using a Sun4 host running UNIX. The LIG method was compared against iterative selection (IS), gray level histograms (GLHs) and two correlation based algorithms on a dozen sample images under three different illumination effects. Overall, the LIG method, while it takes significantly longer, properly thresholds a larger set of images than does any other method examined over the sample images tested
  • Keywords
    computerised pattern recognition; computerised picture processing; badly illuminated images; correlation based algorithms; gray level histograms; gray level thresholding; intensity gradient; iterative selection; local intensity gradient; Computer science; Correlation; Data mining; Histograms; Image analysis; Image processing; Image segmentation; Lighting; Machine intelligence; Pixel;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.85672
  • Filename
    85672