• DocumentCode
    2703944
  • Title

    Localisation of image features using measures of rank distribution

  • Author

    Svalbe, Imants D. ; Evans, Carolyn J.

  • Author_Institution
    Dept. of Phys., Monash Univ., Melbourne, Vic., Australia
  • Volume
    1
  • fYear
    1998
  • fDate
    16-20 Aug 1998
  • Firstpage
    189
  • Abstract
    Measures which characterise local rank distribution can be used to enhance and localise image structure. The diversity and local rank of pixels provide results which are invariant to any strictly order-preserving transformations previously applied to the image data. Localisation of image features to pixel precision is possible through the rank distribution, even with the use of relatively large window sizes. To help detect variations in rank distributions over lengths smaller than the window size, we present methods to sharpen the response of local diversity to image structure. The aim is to enhance image based directly on rank, rather than using conventional linear edge detection. The methods outlined in this paper may be applied to single or multi-band image data
  • Keywords
    computer vision; feature extraction; image enhancement; diversity; grey scale images; image enhancement; image feature localisation; image structure; local rank distribution; pixel precision; Electronic mail; Filters; Morphology; Particle measurements; Physics; Pixel; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
  • Conference_Location
    Brisbane, Qld.
  • ISSN
    1051-4651
  • Print_ISBN
    0-8186-8512-3
  • Type

    conf

  • DOI
    10.1109/ICPR.1998.711112
  • Filename
    711112