Finding local maxima in a pseudo-Euclidean distance transform
Computer Vision, Graphics, and Image Processing
The Euclidean distance transform in arbitrary dimensions
Pattern Recognition Letters
On digital distance transforms in three dimensions
Computer Vision and Image Understanding
Sequential Operations in Digital Picture Processing
Journal of the ACM (JACM)
Surface Skeletons Detected on the D6 Distance Transform
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Simplifying curve skeletons in volume images
Computer Vision and Image Understanding
A Formal Classification of 3D Medial Axis Points and Their Local Geometry
IEEE Transactions on Pattern Analysis and Machine Intelligence
| Hi-index | 0.00 |
A classification of centres of maximal balls (CMBs) in ℤ3 derived from generalizations of the chessboard and city block metrics to 3D, a weighted metric, and the Euclidean metric is presented. Using these metrics, the set of CMBs (the medial axis) can be extracted. One difficulty with skeletonization in 3D is that of guaranteeing reversibility. A reversible skeleton generally consists of both surfaces and curves. Previous attempts to construct connected skeletons including the CMBs uses conditions based on local neighbourhood configurations. However, a local neighbourhood might be too small and, most important, does not allow a consistent definition for surface- and curve-parts of the skeleton. The classification of the CMBs presented in this paper will be a tool for defining which parts of a 3D skeleton are surfaces and curves.