Shape dithering for 3D printing

We present an efficient, purely geometric, algorithmic, and parameter free approach to improve surface quality accuracy in voxel-controlled 3D printing by counteracting quantization artifacts. Such artifacts arise due the discrete voxel sampling of continuous shape used control printer, are characterized low-frequency geometric patterns on surfaces any orientation. They visually disturbing, particularly small prints or smooth surfaces, adversely affect fatigue behavior printed parts. use implicit dithering, displacing part's signed distance field with a high-frequent signal whose amplitude is adapted (anisotropic) print resolution. expand reverse generalized Fourier slice theorem shear transforms, which we leverage optimize blue-noise mask generate anisotropic dither signal. As point process it efficient does not halftoning. evaluate our for efficiency, show its advantages over state art.