• DocumentCode
    2639007
  • Title

    Extraction of maximal inscribed disks from discrete Euclidean distance maps

  • Author

    Ge, Yaorong ; Fitzpatrick, J. Michael

  • Author_Institution
    Bowman Gray Sch. of Med., Wake Forest Univ., Winston-Salem, NC, USA
  • fYear
    1996
  • fDate
    18-20 Jun 1996
  • Firstpage
    556
  • Lastpage
    561
  • Abstract
    Detection of the set of centers of maximal disks is a key step toward generation of accurate skeletons on the basis of distance maps. Algorithms using approximate distance metrics are abundant and their theory has been well established. However, the resulting skeletons may be inaccurate and sensitive to rotation. In this paper, we study methods for detecting maximal disks from distance maps based on the exact Euclidean metric. We first show that no previous algorithm identifies the exact set of discrete maximal disks under Euclidean distance metric. We then propose new algorithms and show that they produce the exact set of maximal disks. The effectiveness of our algorithms is demonstrated with numerous examples
  • Keywords
    computational geometry; image processing; Euclidean distance metric; axis of symmetry; discrete Euclidean distance maps; discrete maximal disks; distance metrics; maximal inscribed disks; shape representation; skeletons; Computer science; Euclidean distance; Geometry; Joining processes; Mathematics; Radiology; Shape; Skeleton; Stress; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1996. Proceedings CVPR '96, 1996 IEEE Computer Society Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-7259-5
  • Type

    conf

  • DOI
    10.1109/CVPR.1996.517127
  • Filename
    517127