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Error Correction for Discrete Tomography

Ceko Matthew, Hajdu Lajos, Tijdeman Rob

Fundamenta Informaticae

2022

Vol. 189, nr 2

91--112

Discrete tomography focuses on the reconstruction of functions from their line sums in a finite number d of directions. In this paper we consider functions f : A → R where A is a finite subset of ℤ2 and R an integral domain. Several reconstruction methods have been introduced in the literature. Recently Ceko, Pagani and Tijdeman developed a fast method to reconstruct a function with the same line sums as f. Up to here we assumed that the line sums are exact. Some authors have developed methods to recover the function f under suitable conditions by using the redundancy of data. In this paper we investigate the case where a small number of line sums are incorrect as may happen when discrete tomography is applied for data storage or transmission. We show how less than d/2 errors can be corrected and that this bound is the best possible. Moreover, we prove that if it is known that the line sums in k given directions are correct, then the line sums in every other direction can be corrected provided that the number of wrong line sums in that direction is less than k/2. [

Assignment and sequencing of parts to autonomous workstations

Lucertini M., Nicolo F., Smriglio S.

Control and Cybernetics

2000

Vol. 29, no 1

221-236

We present an optimization-based coordination protocol among autonomous workstations in a multiprocessor stage devoted to painting of the shutters in a furniture production process. The coordination aims to maximize the number of parallel operations executable at each machine cycle, while fulfilling constraints on the unique-copy tools. The mechanism is derived by a distributed implementation of a bipartite matching algorithm. The resulting procedure is shown to be compatible with the several autonomous decisions characterizing the process.