Quality Evaluation of 3D Printed Surfaces Based on HOG Features

摘要

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.