Finite topology as applied to image analysis
Computer Vision, Graphics, and Image Processing
A topological approach to digital topology
American Mathematical Monthly
A unified linear-time algorithm for computing distance maps
Information Processing Letters
Computer representation of planar regions by their skeletons
Communications of the ACM
New Notions for Discrete Topology
DCGI '99 Proceedings of the 8th International Conference on Discrete Geometry for Computer Imagery
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discrete bisector function and Euclidean skeleton in 2D and 3D
Image and Vision Computing
Exact medial axis with euclidean distance
Image and Vision Computing
A new 3d parallel thinning scheme based on critical kernels
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
Exact euclidean medial axis in higher resolution
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
Appearance radii in medial axis test mask for small planar chamfer norms
DGCI'09 Proceedings of the 15th IAPR international conference on Discrete geometry for computer imagery
New reduced discrete Euclidean nD medial axis with optimal algorithm
Pattern Recognition Letters
3D block-based medial axis transform and chessboard distance transform based on dominance
Image and Vision Computing
Hi-index | 0.00 |
The notion of skeleton plays a major role in shape analysis. Some usually desirable characteristics of a skeleton are: centered, thin, homotopic, and sufficient for the reconstruction of the original object. The Euclidean medial axis presents all these characteristics in a continuous framework. In the discrete case, the exact Euclidean medial axis (MA) is also sufficient for reconstruction and centered. It no longer preserves homotopy but it can be combined with a homotopic thinning to generate homotopic skeletons. The thinness of the MA, however, may be discussed. In this paper, we present the definition of the exact Euclidean medial axis in higher resolution, which has the same properties as the MA but with a better thinness characteristic, against the price of rising resolution. We provide and prove an efficient algorithm to compute it.