• DocumentCode
    3069136
  • Title

    Edge detection and curve enhancement using the facet model and parametrized relaxation labelling

  • Author

    Matalas, I. ; Benjamin, R. ; Kitney, R.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci. Technol. & Med., London, UK
  • Volume
    1
  • fYear
    1994
  • fDate
    9-13 Oct 1994
  • Firstpage
    1
  • Abstract
    We present a method for detecting and labeling the edge structures in digital grey-scale images in two distinct stages: 1) a variant of the cubic facet model detects location, orientation and curvature of the putative edge points; and 2) a relaxation labeling network reinforces meaningful edge structures and suppresses noisy edges. Each node label of this network is a 3D vector parametrizing the orientation and curvature of the corresponding edge point. A hysteresis step in the relaxation process maximizes connected contours. For certain images, prefiltering by adaptive smoothing improves robustness against noise and spatial blurring
  • Keywords
    edge detection; adaptive smoothing; cubic facet model; curve enhancement; digital grey-scale images; edge detection; edge structures; iterative updating; noisy edge suppression; relaxation labelling; Biomedical imaging; Educational institutions; Face detection; Filters; Image edge detection; Labeling; Noise level; Noise robustness; Smoothing methods; Surface fitting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
  • Conference_Location
    Jerusalem
  • Print_ISBN
    0-8186-6265-4
  • Type

    conf

  • DOI
    10.1109/ICPR.1994.576214
  • Filename
    576214