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2018 | OriginalPaper | Buchkapitel

Quality Evaluation of 3D Printed Surfaces Based on HOG Features

verfasst von: Piotr Lech, Jarosław Fastowicz, Krzysztof Okarma

Erschienen in: Computer Vision and Graphics

Verlag: Springer International Publishing

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Abstract

The main purpose of the visual quality assessment of 3D prints is the detection of surface distortions which can be made using various approaches. Nevertheless, a reliable classification of 3D printed samples into low and high quality ones can be troublesome, especially assuming the unknown color of the filament. Such a classification can be efficiently conducted using the approach based on the Histogram of Oriented Gradients (HOG) proposed in this paper. Obtained results are very promising and allow proper classification for the most of the tested samples, especially for some of the most typical distortions.

Vorheriges Kapitel Multi-camera Photometric Simulation for Creation of 3D Object Reconstruction System

Nächstes Kapitel Convolutional Neural Network-Based Action Recognition on Depth Maps

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Titel: Quality Evaluation of 3D Printed Surfaces Based on HOG Features
verfasst von: Piotr Lech
Jarosław Fastowicz
Krzysztof Okarma
Verlag: Springer International Publishing
Buch: Computer Vision and Graphics
Print ISBN: 978-3-030-00691-4

Electronic ISBN: 978-3-030-00692-1

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-030-00692-1_18

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Quality Evaluation of 3D Printed Surfaces Based on HOG Features

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