• DocumentCode
    3326642
  • Title

    Optimal subpixel matching of contour chains and segments

  • Author

    Serra, Bruno ; Berthod, Marc

  • Author_Institution
    INRIA, Sophia-Antipolis, France
  • fYear
    1995
  • fDate
    20-23 Jun 1995
  • Firstpage
    402
  • Lastpage
    407
  • Abstract
    This paper introduces a new general purpose algorithm that allows the optimal geometric match between contours to be determined, that is the transformation yielding a minimal deformation is obtained. The algorithm relies only on the geometric properties of the contours and does not call for any other constraint, so that it is particularly suitable when no parameterization of title deformation is available or desirable. Contour deformation is explicitly incorporated in the computation, allowing for a thorough use of all geometric information available. Moreover, no discretization is involved in the computation, resulting in two main advantages: first, the algorithm is robust to differences in the segmentation of contours and allows the matching of polygonal approximations of contours with very little loss of precision, second, subpixel precision matching can be achieved
  • Keywords
    computational geometry; function approximation; image matching; image segmentation; contour chains; contour deformation; contour segmentation; contour segments; discretization; general purpose algorithm; geometric information; geometric properties; minimal deformation; optimal geometric match; optimal subpixel matching; parameterization; polygonal approximations; subpixel precision matching; Cost function; Displacement measurement; Dynamic programming; Heuristic algorithms; Position measurement; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 1995. Proceedings., Fifth International Conference on
  • Conference_Location
    Cambridge, MA
  • Print_ISBN
    0-8186-7042-8
  • Type

    conf

  • DOI
    10.1109/ICCV.1995.466911
  • Filename
    466911