• DocumentCode
    2605302
  • Title

    The Classification Gradient

  • Author

    Kovalev, Vassili A. ; Petrou, Maria

  • Author_Institution
    Centre for Vision, Speech & Signal Process., Surrey Univ., Guildford
  • Volume
    3
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    830
  • Lastpage
    833
  • Abstract
    We propose a method that uses bootstraping to classify the pixels in the two halves of a sliding window, assuming that if there is a real image boundary separating the two halves, the pixels in the two halves will be classified in two separate classes. The accuracy of the classification is used as a local "gradient". High values of this gradient allow us to detect weak statistical borders in 2D and 3D images
  • Keywords
    image classification; bootstraping; classification accuracy; classification gradient; real image boundary; sliding window; weak statistical borders detection; Computed tomography; Educational institutions; Higher order statistics; Histograms; Humans; Lungs; Pixel; Signal processing; Speech processing; Tumors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.1116
  • Filename
    1699654