An evolutionary algorithm for discrete tomography
Kees Joost Batenburg
- Vol. 151, Iss: 1, pp 36-54
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TLDR
This paper presents an evolutionary algorithm for finding the reconstruction which maximises an evaluation function, representing the ''quality'' of the reconstruction, and shows that the algorithm can be successfully applied to a wide range of evaluation functions.Abstract:
One of the main problems in discrete tomography is the reconstruction of binary matrices from their projections in a small number of directions In this paper we consider a new algorithmic approach for reconstructing binary matrices from only two projections This problem is usually underdetermined and the number of solutions can be very large We present an evolutionary algorithm for finding the reconstruction which maximises an evaluation function, representing the ''quality'' of the reconstruction, and show that the algorithm can be successfully applied to a wide range of evaluation functions We discuss the necessity of a problem-specific representation and tailored search-operators for obtaining satisfactory results Our new search-operators can also be used in other discrete tomography algorithmsread more
Citations
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A framework for generating some discrete sets with disjoint components by using uniform distributions
TL;DR: This paper presents a general framework for generating discrete sets with disjoint connected components using uniform distributions and especially, the uniform random generation of hv-convex discrete sets and Q-conventus discrete sets according to the size of the minimal bounding rectangle are discussed.
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A memetic approach to discrete tomography from noisy projections
TL;DR: A new memetic reconstruction algorithm that generates a set of initial images by network flows, related to two of the input projections, and lets them evolve towards a possible solution, by using crossover and mutation.
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Discrete tomographic reconstruction of binary images with disjoint components using shape information
TL;DR: A backtracking algorithm is developed that works for binary images having components from an arbitrary class and is shown how to extend the algorithm to obtain a branch-and-bound scheme useful to reconstruct images satisfying some further properties as much as possible.
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A cultural algorithm for the representation of mitochondrial population
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Book ChapterDOI
Approximating hv-convex binary matrices and images from discrete projections
TL;DR: Since the problem of reconstructing hv-convex binary matrices from few projections is NP-complete, an iterative approximation based on a longest path and a min-cost/max-flow model is provided.
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David Corne,Marco Dorigo,Fred Glover,Dipankar Dasgupta,Pablo Moscato,Riccardo Poli,Kenneth V. Price +6 more
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