Quality Assessment of 3D Prints Based on Feature Similarity Metrics

  • Krzysztof Okarma
  • Jarosław Fastowicz
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 525)


Visual quality inspection of 3D prints is one of the most recent challenges in image quality assessment domain. One of the natural approaches to this issue seems to be the use of some existing metrics successfully applied to general image quality assessment purposes. Since the application of basic Structural Similarity does not lead to satisfactory quality prediction of 3D prints, in this paper some experimental results obtained using feature based metrics have been presented. Due to the use of different colors of filaments the influence of color to grayscale conversion method has also been analyzed. Proposed approach leads to promising results allowing a reliable prediction of 3D prints quality for different colors of filaments.


Selective Laser Sinter Image Quality Assessment Fuse Deposition Modeling Phase Congruency CIELAB Color Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering, Department of Signal Processing and Multimedia EngineeringWest Pomeranian University of Technology, SzczecinSzczecinPoland

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