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Sequential Projection Selection Methods for Binary Tomography

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Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications (CompIMAGE 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10986))

Abstract

Binary tomography reconstructs binary images from a low number of their projections. Often, there is a freedom how these projections can be chosen which can significantly affect the quality of reconstructions. We apply sequential feature selection methods to find the ‘most informative’ projection set based on a blueprint image. Using various software phantom images, we show that these methods outperform the previously published projection selection algorithms.

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Notes

  1. 1.

    https://www.developer.nvidia.com/cuda-zone.

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Acknowledgements

This research was supported by the project “Integrated program for training new generation of scientists in the fields of computer science”, no EFOP-3.6.3-VEKOP-16-2017-0002. The project has been supported by the European Union and co-funded by the European Social Fund.The authors would like to thank László G. Varga for providing the reconstruction toolbox for the experimental tests.

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Authors and Affiliations

  1. Department of Image Processing and Computer Graphics, University of Szeged, Árpád tér 2, Szeged, 6720, Hungary

    Gábor Lékó & Péter Balázs

Authors
  1. Gábor Lékó
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  2. Péter Balázs
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Corresponding author

Correspondence to Gábor Lékó .

Editor information

Editors and Affiliations

  1. State University of New York at Fredonia, Fredonia, NY, USA

    Reneta P. Barneva

  2. SUNY Buffalo State College, Buffalo, NY, USA

    Valentin E. Brimkov

  3. AGH University of Science and Technology, Cracow, Poland

    Piotr Kulczycki

  4. University of Porto, Porto, Portugal

    João Manuel R. S. Tavares

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Lékó, G., Balázs, P. (2019). Sequential Projection Selection Methods for Binary Tomography. In: Barneva, R., Brimkov, V., Kulczycki, P., Tavares, J. (eds) Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications. CompIMAGE 2018. Lecture Notes in Computer Science(), vol 10986. Springer, Cham. https://doi.org/10.1007/978-3-030-20805-9_7

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  • DOI: https://doi.org/10.1007/978-3-030-20805-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20804-2

  • Online ISBN: 978-3-030-20805-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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