DocumentCode :
1641932
Title :
Flux invariants for shape
Author :
Dimitrov, Pavel ; Damon, James N. ; Siddiqi, Kaleem
Author_Institution :
Sch. of Comput. Sci., McGill Univ., Montreal, Que., Canada
Volume :
1
fYear :
2003
Abstract :
We consider the average outward flux through a Jordan curve of the gradient vector field of the Euclidean distance function to the boundary of a 2D shape. Using an alternate form of the divergence theorem, we show that in the limit as the area of the region enclosed by such a curve shrinks to zero, this measure has very different behaviors at medial points than at non-medial ones, providing a theoretical justification for its use in the Hamilton-Jacobi skeletonization algorithm of Siddiqi et al. (2002). We then specialize to the case of shrinking circular neighborhoods and show that the average outward flux measure also reveals the object angle at skeletal points. Hence, formulae for obtaining the boundary curves, their curvatures, and other geometric quantities of interest, can be written in terms of the average outward flux limit values at skeletal points. Thus this measure can be viewed as a Euclidean invariant for shape description: it can be used to both detect the skeleton from the Euclidean distance function, as well as to explicitly reconstruct the boundary from it. We illustrate our results with several numerical simulations.
Keywords :
Jacobian matrices; computer vision; curve fitting; edge detection; feature extraction; image reconstruction; image thinning; object recognition; 2D shape boundary; Euclidean distance function; Euclidean invariant; Hamilton-Jacobi skeletonization algorithm; Jordan curve; average outward flux measure; boundary curve; boundary reconstruction; circular neighborhood; computer vision; divergence theorem; flux invariant; geometric quantity; gradient vector field; medial point; numerical simulation; object angle; outward flux limit value; region area; shape description; shape representation; skeletal point; Area measurement; Biomedical imaging; Computer science; Computer vision; Euclidean distance; Image reconstruction; Mathematics; Numerical simulation; Shape measurement; Skeleton;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-1900-8
Type :
conf
DOI :
10.1109/CVPR.2003.1211439
Filename :
1211439
Link To Document :
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