Prediction of the layered ink layout for 3D printers considering a desired skin color and line spread function

Abstract We propose a layout estimation method for multi-layered ink using measurement of the line spread function (LSF) and machine learning. The three-dimensional printing market general consumers focuses on reproduction realistic appearance. In particular, human skin, it is important to control translucency by adopting multilayer structure. Traditionally, layer design has depended experience designers. We, therefore, developed an efficient provide arbitrary skin color translucency. our method, we create patches measure LSF as metric translucency, employ neural network trained with data estimate layout. As evaluation, measured from computer-graphics-created fabricate estimated layout; evaluation root-mean-square error showed that can obtain are close target.