Decision Trees in Binary Tomography for Supporting the Reconstruction of hv-Convex Connected Images
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Convex-set perimeter estimation from its two projections
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
Discrete Q-convex sets reconstruction from discrete point X-rays
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
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In some applications, the tomographic reconstruction is not an end in itself. When the goal is rather to gather information about the object being studied, the question is if it is more interesting to directly extract these information from the projections without the reconstructing step. We would then know if less projections are needed to directly get the information than to reconstruct the object. In this paper, we address the problem of extracting quantitative information about an object namely an estimation of its area, an upper and a lower bound to the perimeter given its projections from point sources.