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C_AssesSeg Concurrent Computing Version of AssesSeg: A Benchmark Between the New and Previous Version

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Computational Science and Its Applications – ICCSA 2017 (ICCSA 2017)

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Abstract

This paper presents the capabilities of a command line tool (.exe) created to assess the quality of segmented digital images. The executable source code, called AssesSeg (Assess Segmentation), was written in Python 2.7 using only open source libraries. AssesSeg implements a modified version of the supervised discrepancy measure named Euclidean Distance 2 (ED2) and was tested on different satellite images (Sentinel-2, Landsat 8, WorldView-2 and WorldView-3). The segmentation was applied to plastic covered greenhouse detection in the south of Spain (Almería). AssesSeg 2.0 was compared with the previous version computing time. The comparisons showed how the new version can benefit from modern multi-core CPU.

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Acknowledgement

This work was supported by the Spanish Ministry of Economy and Competitiveness (Spain) and the European Union FEDER funds (Grant Reference AGL2014-56017-R). It takes part of the general research lines promoted by the Agrifood Campus of International Excellence ceiA3.

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Authors and Affiliations

  1. Politecnico di Bari, Via Orabona 7, 70125, Bari, Italy

    Antonio Novelli & Eufemia Tarantino

  2. Department of Engineering, University of Almería, 04120, Almería, Spain

    Manuel A. Aguilar, Fernando J. Aguilar & Abderrahim Nemmaoui

Authors
  1. Antonio Novelli
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  2. Manuel A. Aguilar
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  3. Fernando J. Aguilar
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  4. Abderrahim Nemmaoui
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  5. Eufemia Tarantino
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Corresponding author

Correspondence to Eufemia Tarantino .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Trieste, Trieste, Italy

    Giuseppe Borruso

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  9. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  10. University of Trieste, Trieste, Italy

    Alfredo Cuzzocrea

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Novelli, A., Aguilar, M.A., Aguilar, F.J., Nemmaoui, A., Tarantino, E. (2017). C_AssesSeg Concurrent Computing Version of AssesSeg: A Benchmark Between the New and Previous Version. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10407. Springer, Cham. https://doi.org/10.1007/978-3-319-62401-3_4

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  • DOI: https://doi.org/10.1007/978-3-319-62401-3_4

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  • Online ISBN: 978-3-319-62401-3

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