| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6941276 | Pattern Recognition Letters | 2014 | 8 Pages |
Abstract
Generalizations of various random tessellation models generated by Poisson point processes are introduced, and their functional probability P(K) is given. They are obtained from Boolean random function models, and alternatively from a geodesic distance, providing a generic way of simulation of a wide range of random tessellations, as illustrated in the paper.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Dominique Jeulin,