• DocumentCode
    304582
  • Title

    A nonparametric approach for detecting lines and curves

  • Author

    Lim, Gek ; Alder, Michael

  • Author_Institution
    Centre for Intelligent Inf. Process. Syst., Western Australia Univ., Nedlands, WA, Australia
  • Volume
    1
  • fYear
    1996
  • fDate
    16-19 Sep 1996
  • Firstpage
    837
  • Abstract
    The process of detecting lines and curves in an image is an important component of many pattern recognition and computer vision applications. There are well understood approaches to finding curves from a parametrised space of curves. In many practical cases, however, there exist arbitrary shape curves, and different types of curves in the same image. In addition, local perturbation noise can be added to the images. We propose a nonparametric method to overcome the above mentioned problems. The method is based on local modeling of the data. It does not require the specification of a parametric space of curves. It can be used to detect arbitrary curves and thus has a wider applicability than parametric approaches
  • Keywords
    computer vision; edge detection; arbitrary shape curves; computer vision; curves detection; image processing; lines detection; local modeling; local perturbation noise; nonparametric approach; pattern recognition; Application software; Australia; Clustering algorithms; Computer vision; Information processing; Intelligent systems; Noise shaping; Pattern recognition; Pixel; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1996. Proceedings., International Conference on
  • Conference_Location
    Lausanne
  • Print_ISBN
    0-7803-3259-8
  • Type

    conf

  • DOI
    10.1109/ICIP.1996.559629
  • Filename
    559629