• DocumentCode
    2631080
  • Title

    Thresholding using an illumination model

  • Author

    Parker, J.R. ; Jennings, C. ; Salkauskas, A.G.

  • Author_Institution
    Calgary Univ., Alta., Canada
  • fYear
    1993
  • fDate
    20-22 Oct 1993
  • Firstpage
    270
  • Lastpage
    273
  • Abstract
    Most grey-level thresholding methods produce good results in situations where the illumination gradient in the original raster image is regular and not too large. In other cases, such as a large linear change in illumination, a satisfactory bi-level image cannot be produced. If the object pixels can be identified in a variety of positions throughout the image, these can be used to construct a surface whose height is related to illumination at each pixel. This estimate can be used to produce a threshold for each pixel. The method described here uses the Shen-Castan edge detector to identify object pixels, and creates a surface using a moving least squares method that can be used to threshold the image
  • Keywords
    edge detection; feature extraction; image segmentation; least mean squares methods; lighting; Shen-Castan edge detector; bi-level image; grey-level thresholding methods; illumination gradient; illumination model; moving least squares method; object pixels; raster image; Computer science; Data mining; Detectors; Frequency; Image edge detection; Least squares methods; Lighting; Mathematics; Object detection; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
  • Conference_Location
    Tsukuba Science City
  • Print_ISBN
    0-8186-4960-7
  • Type

    conf

  • DOI
    10.1109/ICDAR.1993.395734
  • Filename
    395734