Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Simulating the Grassfire Transform Using an Active Contour Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ridge points in Euclidean distance maps
Pattern Recognition Letters
Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shock Graphs and Shape Matching
International Journal of Computer Vision
A tree-edit-distance algorithm for comparing simple, closed shapes
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
International Journal of Computer Vision
Divergence-Based Medial Surfaces
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Efficiently Computing Weighted Tree Edit Distance Using Relaxation Labeling
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Proceedings of the Workshop on Geometry and Robotics
Symmetry Maps of Free-Form Curve Segments via Wave Propagation
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
A shock grammar for recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
View-Based 3-D Object Recognition using Shock Graphs
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Recognition of Shapes by Editing Their Shock Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
A skeletal measure of 2D shape similarity
Computer Vision and Image Understanding
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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 inward evolving boundary flux 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.