Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parts of Visual Form: Computational Aspects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing and simplifying 2D and 3D continuous skeletons
Computer Vision and Image Understanding
Handbook of discrete and computational geometry
Handbook of discrete and computational geometry
Teddy: a sketching interface for 3D freeform design
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Hierarchical Decomposition of Multiscale Skeletons
IEEE Transactions on Pattern Analysis and Machine Intelligence
Untangling the Blum Medial Axis Transform
International Journal of Computer Vision - Special Issue on Research at the University of North Carolina Medical Image Display Analysis Group (MIDAG)
Representation and detection of deformable shapes
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Decomposition of Two-Dimensional Shapes by Graph-Theoretic Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rectification of the chordal axis transform and a new criterion for shape decomposition
DGCI'05 Proceedings of the 12th international conference on Discrete Geometry for Computer Imagery
3D shape recursive decomposition by Poisson equation
Pattern Recognition Letters
A framework for perceptual image analysis
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
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Skeletonization and parts-based decomposition are important to the analysis, characterization, and recognition of shapes. In earlier works we proposed the chordal axis transform (CAT), based on constrained Delaunay triangulations (CDT), for analyzing discrete shapes. In this paper, we refine the CAT skeleton to have smoother branches and stable branch points of any degree based on approximate co-circularity of edge-adjacent triangles. We also introduce new criteria for obtaining visually meaningful shape decompositions using approximate co-circularity and a discrete axial derivative for shapes based on their CDTs.