Generating skeletons and centerlines from the distance transform
CVGIP: Graphical Models and Image Processing
Building skeleton models via 3-D medial surface/axis thinning algorithms
CVGIP: Graphical Models and Image Processing
Skeletonization via distance maps and level sets
Computer Vision and Image Understanding
A Method for Obtaining Skeletons Using a Quasi-Euclidean Distance
Journal of the ACM (JACM)
Efficient Skeletonization of Volumetric Objects
IEEE Transactions on Visualization and Computer Graphics
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Robust Feature Detection and Local Classification for Surfaces Based on Moment Analysis
IEEE Transactions on Visualization and Computer Graphics
A 3D fully parallel surface-thinning algorithm
Theoretical Computer Science
Study on processing for seam image based on CCD vision sensing
AEE'07 Proceedings of the 6th conference on Applications of electrical engineering
Discrete scale axis representations for 3D geometry
ACM SIGGRAPH 2010 papers
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
Isthmus-based 6-directional parallel thinning algorithms
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
Skeletonization and distance transforms of 3D volumes using graphics hardware
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
Generalized distance transforms and skeletons in graphics hardware
VISSYM'04 Proceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization
Image-based edge bundles: simplified visualization of large graphs
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
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A robust and efficient method in 2D and 3D for the calculation of skeletons for arbitrary objects is presented. The method is based on the calculation of the distance function with respect to the object boundary. This is combined, in a post processing step, with a new indicator to identify the skeleton, which coincides with the singularity set of the distance map. The indicator is defined as a suitable function of certain local momenta of this distance map and allows a robust and accurate computation of the distance from the skeleton set. This distance is then extended, again via the level set method, onto the whole space. Several applications in 2D and 3D are presented.