Artificial Intelligence
A One-Pass Two-Operation Process to Detect the Skeletal Pixels on the 4-Distance Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simulating the Grassfire Transform Using an Active Contour Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Continuous skeleton computation by Voronoi diagram
CVGIP: Image Understanding
Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating skeletons and centerlines from the distance transform
CVGIP: Graphical Models and Image Processing
On the Generation of Skeletons from Discrete Euclidean Distance Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
Convexity rule for shape decomposition based on discrete contour evolution
Computer Vision and Image Understanding
Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shock Graphs and Shape Matching
International Journal of Computer Vision
An augmented Fast Marching Method for computing skeletons and centerlines
VISSYM '02 Proceedings of the symposium on Data Visualisation 2002
International Journal of Computer Vision
A shock grammar for recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Recognition of Shapes by Editing Their Shock Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Axis-Based Representation for Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Shape Representation and Classification Using the Poisson Equation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Classification Using the Inner-Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discrete bisector function and Euclidean skeleton in 2D and 3D
Image and Vision Computing
Path Similarity Skeleton Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
2D Shape Matching by Contour Flexibility
IEEE Transactions on Pattern Analysis and Machine Intelligence
Disconnected Skeleton: Shape at Its Absolute Scale
IEEE Transactions on Pattern Analysis and Machine Intelligence
A skeleton family generator via physics-based deformable models
IEEE Transactions on Image Processing
Learning Context-Sensitive Shape Similarity by Graph Transduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Groupwise Medial Axis Transform for Fuzzy Skeletonization and Pruning
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A Width-Independent Fast Thinning Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Using Anisotropic Diffusion for Skeleton Extraction
International Journal of Computer Vision
On the generation and pruning of skeletons using generalized Voronoi diagrams
Pattern Recognition Letters
Toward perception-based shape decomposition
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
A skeleton pruning algorithm based on information fusion
Pattern Recognition Letters
Empirical mode decomposition on skeletonization pruning
Image and Vision Computing
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We propose a novel significance measure for skeleton pruning, called bending potential ratio (BPR), in which the decision regarding whether a skeletal branch should be pruned or not is based on the context of the boundary segment that corresponds to the branch. By considering this contextual information, we can better evaluate the contribution of the boundary segment to the overall shape, which generally depends on its particular location within the whole contour (i.e., a segment may be considered to be insignificant in one place while it may be considered as a feature elsewhere). The BPR is a measure of the significance of contour segments in such context, and depicts the bending potential of a contour segment. Unlike other significance measures that only contain local shape information, the BPR evaluates both local and global shape information. Thus, it is insensitive to local boundary deformation. In addition, we also present a scheme for skeleton growing, which integrates pruning based on the BPR measurement. Our experiments demonstrate that the skeletons obtained by the proposed algorithm are medially placed and connected. We also demonstrate that shapes reconstructed from these skeletons are very close to the original shapes. Moreover, the BPR measure yields a natural multi-scale skeletal representation.