The number of convex polyominoes reconstructible from their orthogonal projections
Proceedings of the 6th conference on Formal power series and algebraic combinatorics
Reconstructing hv-convex polyominoes from orthogonal projections
Information Processing Letters
The reconstruction of binary patterns from their projections
Communications of the ACM
Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks
Stability and instability in discrete tomography
Digital and image geometry
An evolutionary algorithm for discrete tomography
Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
An Evolutionary Approach for Object-Based Image Reconstruction Using Learnt Priors
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
A benchmark set for the reconstruction of hv-convex discrete sets
Discrete Applied Mathematics
Discrete tomography reconstruction through a new memetic algorithm
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
A memetic approach to discrete tomography from noisy projections
Pattern Recognition
A memetic island model for discrete tomography reconstruction
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
An island strategy for memetic discrete tomography reconstruction
Information Sciences: an International Journal
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The aim of this paper is the description of an experiment carried out to verify the robustness of two different approaches for the reconstruction of convex polyominoes in discrete tomography. This is a new field of research, because it differs from classic computerized tomography, and several problems are still open. In particular, the stability problem is tackled by using both a modified version of a known algorithm and a new genetic approach. The effect of both, instrumental and quantization noises has been considered too.