On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Representation by Multiscale Contour Approximation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Geometric heat equation and nonlinear diffusion of shapes and images
Computer Vision and Image Understanding
Convexity rule for shape decomposition based on discrete contour evolution
Computer Vision and Image Understanding
Learning Visual Models from Shape Contours Using Multiscale Convex/Concave Structure Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Review of Nonlinear Diffusion Filtering
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Mustererkennung 1995, 17. DAGM-Symposium
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
A New Contour-Based Approach to Object Recognition for Assembly Line Robots
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
A discrete geometry approach for dominant point detection
Pattern Recognition
Improved stochastic competitive Hopfield network for polygonal approximation
Expert Systems with Applications: An International Journal
KI'11 Proceedings of the 34th Annual German conference on Advances in artificial intelligence
Skeleton pruning by contour partitioning
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
Homotopic object reconstruction using natural neighbor barycentric coordinates
Transactions on Computational Science XIV
| Hi-index | 0.00 |
We propose a simple approach to evolution of polygonal curves that is specially designed to fit discrete nature of curves in digital images. It leads to simplification of shape complexity with no blurring (i.e., shape rounding) effects and no dislocation of relevant features. Moreover, in our approach the problem to determine the size of discrete steps for numerical implementations does not occur, since our evolution method leads in a natural way to a finite number of discrete evolution steps which are just the iterations of a basic procedure of vertex deletion.