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
Link To Document