DocumentCode :
398549
Title :
Curvature dependent skeletonization
Author :
Torsello, Andrea ; Hancock, Edwin R.
Author_Institution :
Dept. of Comput. Sci., York Univ., North York, Ont., Canada
Volume :
1
fYear :
2003
fDate :
14-17 Sept. 2003
Abstract :
The Hamilton-Jacobi approach has proved to be a powerful and elegant method for extracting the skeleton of a shape. The approach is based on the fact that the dynamics of the inward evolving boundary is conservative everywhere except at skeletal points. Nonetheless this method appears to overlook the fact that the linear density of the evolving boundary front is not constant where the front is curved. In this paper we present an analysis which takes into account variations of density due to boundary curvature. This yields a skeletonization algorithm that is both better localized and less susceptible to boundary noise than the Hamilton-Jacobi method.
Keywords :
Jacobian matrices; image thinning; multidimensional signal processing; partial differential equations; Hamilton-Jacobi approach; boundary curvature; curvature dependent skeletonization; partial differential equations; skeleton shape extraction; Blades; Computer science; Differential equations; Ear; Electric shock; Geometry; Noise shaping; Partial differential equations; Shape; Skeleton;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on
ISSN :
1522-4880
Print_ISBN :
0-7803-7750-8
Type :
conf
DOI :
10.1109/ICIP.2003.1246967
Filename :
1246967
Link To Document :
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