Quality assessment of 3D prints based on feature similarity metrics

Abstract

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.