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A Memetic Island Model for Discrete Tomography Reconstruction

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Fuzzy Logic and Applications (WILF 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6857))

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Abstract

Soft computing is a term indicating a coalition of methodologies, and its basic dogma is that, in general, better results can be obtained through the use of constituent methodologies in combination, rather than in a stand alone mode. Evolutionary computing belongs to this coalition, and thus memetic algorithms. Here, we present a combination of several instances of a recently proposed memetic algorithm for discrete tomography reconstruction, based on the island model parallel implementation. The combination is motivated by the fact that, even though the results of the recently proposed approach are finally better and more robust compared to other approaches, we advised that its major drawback was the computational time. The underlying combination strategy consists in separated populations of agents evolving by means of different processes which share some individuals, from time to time. Experiments were performed to test the benefits of this paradigm in terms of computational time and correctness of the solutions.

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References

  1. Kak, A.C., Slaney, M.: Principles of Computerized Tomography Imaging. Society for Industrial Mathematics (2001)

    Google Scholar 

  2. Herman, G.T., Kuba, A. (eds.): Discrete Tomography: Foundations, Algorithms, and Applications. Birkhäuser, Basel (1999)

    MATH  Google Scholar 

  3. Gale, D.: A theorem on flows in networks. Pacific Journal of Mathematics 7, 1073–1082 (1957)

    Article  MathSciNet  MATH  Google Scholar 

  4. Ryser, H.J.: Combinatorial properties of matrices of zeros and ones. Canadian Journal of Mathematics 9, 371–377 (1957)

    Article  MathSciNet  MATH  Google Scholar 

  5. Gardner, R.J., Gritzmann, P., Prangenberg, D.: On the computational complexity of reconstructing lattice sets from their X-rays. Discrete Mathematics 202, 45–71 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  6. Wang, B., Zhang, F.: On the precise number of (0,1)-matrices in U(R,S). Discrete Mathematics 187, 211–220 (1998)

    Article  MathSciNet  Google Scholar 

  7. Frosini, A., Nivat, M., Vuillon, L.: An introductive analysis of periodical discrete sets from a tomographical point of view. Theoretical Computer Science 347(1–2), 370–392 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  8. Svalbe, I., van der Spek, D.: Reconstruction of tomographic images using analog projections and the digital Radon transform. Linear Algebra and its Applications 339, 125–145 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  9. Anstee, R.P.: The network flows approach for matrices with given row and column sums. Discrete Mathematics 44, 125–138 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  10. Balázs, P., Balogh, E., Kuba, A.: Reconstruction of 8-connected but not 4-connected hv-convex discrete sets. Discrete Applied Mathematics 147, 149–168 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  11. Herman, G.T., Kuba, A.: Discrete Tomography: Foundations, Algorithms, and Applications. In: Binary Tomography Using Gibbs Priors, pp. 191–212. Birkhäuser, Basel (1999)

    Google Scholar 

  12. Valenti, C.: A genetic algorithm for discrete tomography reconstruction. Genetic Programming and Evolvable Machines 9, 85–96 (2008)

    Article  Google Scholar 

  13. Batenburg, J.K.: An evolutionary algorithm for discrete tomography. Discrete Applied Mathematics 151, 36–54 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  14. Balázs, P., Gara, M.: An Evolutionary Approach for Object-Based Image Reconstruction Using Learnt Priors. In: Salberg, A.-B., Hardeberg, J.Y., Jenssen, R. (eds.) SCIA 2009. LNCS, vol. 5575, pp. 520–529. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  15. Moscato, P.: On evolution, search, optimization, genetic algorithms and martial arts: towards memetic algorithms. Caltech Concurrent Computation Program, C3P Report 826 (1989)

    Google Scholar 

  16. Corne, D., Dorigo, M., Glover, F.: New ideas in optimization. McGraw-Hill, New York (1999)

    Google Scholar 

  17. Eklund, S.E.: A massively parallel architecture for distributed genetic algorithms. Parallel Computing 30(5–6), 647–676 (2004)

    Article  Google Scholar 

  18. Di Gesù, V., Lo Bosco, G., Millonzi, F., Valenti, C.: A memetic approach to discrete tomography from noisy projections. Pattern Recognition 43(9), 3073–3082 (2010)

    Article  Google Scholar 

  19. Isgró, F., Tegolo, D.: A distributed genetic algorithm for restoration of vertical line scratches. Parallel Computing 34(12), 727–734 (2008)

    Article  Google Scholar 

  20. Ryser, H.J.: Combinatorial mathematics. The carus mathematical monographs. Ch.6, (14). MAA (1963)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dipartimento di Matematica e Informatica, Università di Palermo, via Archirafi 34, 90123, Italy

    Marco Cipolla, Giosuè Lo Bosco, Filippo Millonzi & Cesare Valenti

Authors
  1. Marco Cipolla
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  2. Giosuè Lo Bosco
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  3. Filippo Millonzi
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  4. Cesare Valenti
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Editor information

Editors and Affiliations

  1. Computer Science Department, University of Bari, Via E. Orabona, 4, 70125, Bari, Italy

    Anna Maria Fanelli

  2. Department of Electrical and Computer Engineering, University of Alberta, T6G 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

  3. Department of Apllied Science, University of Naples Parthenope, Centro Direzionale Is. C4, 80143, Naples, Italy

    Alfredo Petrosino

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© 2011 Springer-Verlag Berlin Heidelberg

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Cipolla, M., Bosco, G.L., Millonzi, F., Valenti, C. (2011). A Memetic Island Model for Discrete Tomography Reconstruction. In: Fanelli, A.M., Pedrycz, W., Petrosino, A. (eds) Fuzzy Logic and Applications. WILF 2011. Lecture Notes in Computer Science(), vol 6857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23713-3_33

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  • DOI: https://doi.org/10.1007/978-3-642-23713-3_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23712-6

  • Online ISBN: 978-3-642-23713-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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