• DocumentCode
    3061594
  • Title

    Chamfer masks: discrete distance functions, geometrical properties and optimization

  • Author

    Thiel, Edouard ; Montanvert, Annick

  • Author_Institution
    IMAG, Univ. Joseph Fourier, Grenoble, France
  • fYear
    1992
  • fDate
    30 Aug-3 Sep 1992
  • Firstpage
    244
  • Lastpage
    247
  • Abstract
    The chamfer distances are based on the definition of masks whose size can change depending on the quality of the approximation which is expected, compared to the Euclidean distance. The authors show the induced geometrical properties of the generated distance images, and calculate the required properties of the mask to ensure that they define a distance function. Then they show how to optimize the masks directly in discrete space, and finally, present some main applications
  • Keywords
    computational geometry; image processing; optimisation; Euclidean distance; chamfer distances; chamfer masks; discrete distance functions; distance images; image processing; induced geometrical properties; optimization; Aggregates; Application software; Cities and towns; Constraint theory; Euclidean distance; Extraterrestrial measurements; Image analysis; Image generation; Image sampling; Lattices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on
  • Conference_Location
    The Hague
  • Print_ISBN
    0-8186-2920-7
  • Type

    conf

  • DOI
    10.1109/ICPR.1992.201971
  • Filename
    201971