@InProceedings{ICCS2020_3Dp,
author="Fastowicz, Jaros{\l}aw
and Lech, Piotr
and Okarma, Krzysztof",
editor="Krzhizhanovskaya, Valeria V.
and Z{\'a}vodszky, G{\'a}bor
and Lees, Michael H.
and Dongarra, Jack J.
and Sloot, Peter M. A.
and Brissos, S{\'e}rgio
and Teixeira, Jo{\~a}o",
title="Combined Metrics for Quality Assessment of 3D Printed Surfaces for Aesthetic Purposes: Towards Higher Accordance with Subjective Evaluations",
booktitle="Computational Science -- ICCS 2020",
year="2020",
publisher="Springer International Publishing",
address="Cham",
pages="326--339",
abstract="Objective quality assessment for 3D printing purposes may be considered as one of the most useful applications of machine vision in smart monitoring related to the development of the Industry 4.0 solutions. During recent years several approaches have been proposed, assuming observing the side surfaces, mainly based on the analysis of the regularity of visible patterns, which represent the consecutive printed layers. These methods, based on the use of general purpose image quality assessment (IQA) metrics, Hough transform, entropy and texture analysis, make it possible to classify the printed samples, independently of the filament's colour, into low and high quality classes, with the use of photos or 3D scans of the side surfaces.",
isbn="978-3-030-50436-6"
}