Reconstructing convex polyominoes from horizontal and vertical projections
Theoretical Computer Science
An efficient implementation of a scaling minimum-cost flow algorithm
Journal of Algorithms
On the precise number of (0,1)-matrices in U(R,S)
Discrete Mathematics
Reconstructing hv-convex polyominoes from orthogonal projections
Information Processing Letters
On the comptational complexity of determining polyatomic structures by X-rays
Theoretical Computer Science
Reconstruction of domino tiling from its two orthogonal projections
Theoretical Computer Science
The reconstruction of polyominoes from their orthogonal projections
Information Processing Letters
Theoretical Computer Science
An evolutionary algorithm for discrete tomography
Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
Optimization and reconstruction of hv-convex (0,1)-matrices
Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
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We study the problem of reconstructing hv-convex binary matrices from few projections. We solve a polynomial time case and we determine some properties of the hv-convex matrices. Since the problem is NP-complete, we provide an iterative approximation based on a longest path and a min-cost/max-flow model. The experimental results show that the reconstruction algorithm performs quite well.