• DocumentCode
    304580
  • Title

    Unsupervised contour estimation

  • Author

    Figueiredo, Mário A T ; Leitão, José M N

  • Author_Institution
    Dept. de Engenharia Electrotecnica e de Comput., Inst. Superior Tecnico, Lisbon, Portugal
  • Volume
    1
  • fYear
    1996
  • fDate
    16-19 Sep 1996
  • Firstpage
    821
  • Abstract
    We introduce a fully adaptive active contour model in which no parameters have to be set a priori or tuned by the user. It is based on elliptic Fourier contour description and on the minimum description length (MDL) principle. The proposed technique estimates all the observation model parameters (e.g., noise variances), the order of the contour description (number of Fourier coefficients), and the contour itself
  • Keywords
    Fourier series; adaptive estimation; edge detection; parameter estimation; Fourier coefficients; MDL; adaptive active contour model; algorithms; contour description; edge detection; elliptic Fourier contour description; minimum description length principle; noise variances; observation model parameters; parameter estimation; unsupervised contour estimation; Active contours; Bayesian methods; Computer vision; Deformable models; Fourier series; Frequency; Shape; Telecommunications;
  • 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.1996.559625
  • Filename
    559625