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- Publisher
- Springer Journals
- Copyright
- Copyright © 2014 by Springer International Publishing Switzerland
- Subject
- Computer Science; Artificial Intelligence (incl. Robotics); Mathematics, general; Computer Science, general; Statistical Physics, Dynamical Systems and Complexity
- ISSN
- 1012-2443
- eISSN
- 1573-7470
- DOI
- 10.1007/s10472-014-9440-8
- Publisher site
- See Article on Publisher Site
Abstract
In binary tomography, the goal is to reconstruct binary images from a small set of their projections. This task can be underdetermined, meaning that several binary images can have the same projections, especially when only one or two projections are given. On the other hand, it is known that a binary image can be exactly reconstructed from its morphological skeleton when all skeletal labels are known. However, if only the skeletal points are given, different labellings yield different reconstructed images. In this paper, we consider a mixture of the above problems, reconstructing a binary image from few projections and the morphological skeleton. We show that the problem is NP-complete, yet a result with low projection and pixel error usually can be achieved, even if only a single projection is available. Three different variants of a method based on Simulated Annealing are developed and compared with respect to reconstruction time and error using artificial binary images.
Journal
Annals of Mathematics and Artificial Intelligence – Springer Journals
Published: Nov 21, 2014