A comment on “a fast parallel algorithm for thinning digital patterns”
Communications of the ACM - The MIT Press scientific computation series
Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
Ridge points in Euclidean distance maps
Pattern Recognition Letters
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Computer Vision and Image Understanding
Zoom-invariant vision of figural shape: the mathematics of cores
Computer Vision and Image Understanding
Zoom-invariant vision of figural shape: effects on cores of image disturbances
Computer Vision and Image Understanding
Shock Graphs and Shape Matching
International Journal of Computer Vision
A fast parallel algorithm for thinning digital patterns
Communications of the ACM
International Journal of Computer Vision
Hierarchical Decomposition and Axial Shape Description
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Low Complexity Fully Parallel Thinning Algorithm
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Local Symmetries of Shapes in Arbitrary Dimension
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Multiscale Medial Loci and Their Properties
International Journal of Computer Vision - Special Issue on Research at the University of North Carolina Medical Image Display Analysis Group (MIDAG)
Recognition of Shapes by Editing Their Shock Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gray skeletons and segmentation of shapes
Computer Vision and Image Understanding
Finding shape axes using magnetic fields
IEEE Transactions on Image Processing
Strategies for shape matching using skeletons
Computer Vision and Image Understanding
| Hi-index | 0.01 |
Many algorithms suppress skeleton associated with boundary perturbation by preventing their formation or by costly branch pruning. This work proposes a novel concept of structural and textural skeletons. The former is associated with the general shape structure and the latter with boundary perturbations. These skeletons remain disconnected to facilitate gross shape matching without the need for branch pruning. They are extracted from a multiresolution gradient vector field that is efficiently generated within a pyramidal framework. Experimental results show that these skeletons are scale and rotation invariant. They are less affected by boundary noise compared to skeletons extracted by popular iterative and non-iterative techniques.