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Parallel Processing of Color Digital Images for Linguistic Description of Their Content

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Parallel Processing and Applied Mathematics (PPAM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10777))

Abstract

This paper presents different aspects of parallelization of a problem of processing color digital images in order to generate linguistic description of their content. A parallel architecture of an intelligent image recognition system is proposed. Fuzzy classification and inference is performed in parallel, based on the CIE chromaticity color model and granulation approach. In addition, the parallelization concerns e.g. processing a large collection of images or parts of a single image.

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Author information

Authors and Affiliations

  1. Institute of Computer and Information Sciences, Czestochowa University of Technology, 42-201, Czestochowa, Poland

    Krzysztof Wiaderek & Danuta Rutkowska

  2. Information Technology Institute, University of Social Sciences, 90-113, Lodz, Poland

    Danuta Rutkowska

  3. Department of Mathematics and Natural Sciences, Blekinge Institute of Technology, S-37179, Karlskrona, Sweden

    Elisabeth Rakus-Andersson

Authors
  1. Krzysztof Wiaderek
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  2. Danuta Rutkowska
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  3. Elisabeth Rakus-Andersson
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Corresponding author

Correspondence to Krzysztof Wiaderek .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Czestochowa, Poland

    Roman Wyrzykowski

  2. University of Tennessee, Knoxville, Tennessee, USA

    Jack Dongarra

  3. University of Southern California, Marina Del Rey, California, USA

    Ewa Deelman

  4. Czestochowa University of Technology, Czestochowa, Poland

    Konrad Karczewski

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Wiaderek, K., Rutkowska, D., Rakus-Andersson, E. (2018). Parallel Processing of Color Digital Images for Linguistic Description of Their Content. In: Wyrzykowski, R., Dongarra, J., Deelman, E., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2017. Lecture Notes in Computer Science(), vol 10777. Springer, Cham. https://doi.org/10.1007/978-3-319-78024-5_47

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  • DOI: https://doi.org/10.1007/978-3-319-78024-5_47

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  • Print ISBN: 978-3-319-78023-8

  • Online ISBN: 978-3-319-78024-5

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