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Color Independent Quality Assessment of 3D Printed Surfaces Based on Image Entropy

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Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017 (CORES 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 578))

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Abstract

The paper is focused on the issue of visual quality assessment of 3D printed surfaces which can be helpful in detection of quality decrease during the printing process as well as the quality inspection of previously printed objects. The basic assumption of the proposed approach is the fact that each distortion of the regular patterns, visible on the side surfaces of objects printed using Fused Deposition Modeling (FDM) technology, causes the increase of the local image entropy. However, due to different colors of the filaments used in our experiments, a reliable prediction of the absolute entropy values can be troublesome. The proposed solution utilizes the combined quality indicator based on the entropy and its variance calculated for the hue component, as well as for the RGB channels, depending on the color of the filament, allowing proper detection of low quality surfaces regardless of the filament’s color.

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Authors and Affiliations

  1. Department of Signal Processing and Multimedia Engineering, Faculty of Electrical Engineering, West Pomeranian University of Technology, Szczecin, 26. Kwietnia 10, 71-126, Szczecin, Poland

    Krzysztof Okarma & Jarosław Fastowicz

Authors
  1. Krzysztof Okarma
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  2. Jarosław Fastowicz
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Corresponding author

Correspondence to Krzysztof Okarma .

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Editors and Affiliations

  1. Department of Systems and Computer Networks, Wrocław University of Technology, Wrocław, Poland

    Marek Kurzynski

  2. Department of Systems and Computer Networks, Wrocław University of Technology, Wroclaw, Poland

    Michal Wozniak

  3. Department of Systems and Computer Networks, Wrocław University of Technology , Wroclaw, Poland

    Robert Burduk

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Okarma, K., Fastowicz, J. (2018). Color Independent Quality Assessment of 3D Printed Surfaces Based on Image Entropy. In: Kurzynski, M., Wozniak, M., Burduk, R. (eds) Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017. CORES 2017. Advances in Intelligent Systems and Computing, vol 578. Springer, Cham. https://doi.org/10.1007/978-3-319-59162-9_32

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  • DOI: https://doi.org/10.1007/978-3-319-59162-9_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59161-2

  • Online ISBN: 978-3-319-59162-9

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