Surface attributes driven volume segmentation for 3D-printing

• Published in: Computers & graphics Vol. 100; pp. 43 - 53
• Main Authors: Liu, Xin, Xian, Chuhua, Jin, Shuo, Li, Guiqing
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-11-2021; Elsevier Science Ltd
• Subjects: 3D-printing; Assemblability; Evolutionary algorithms; Evolutionary computation; Multi-material fabrication; Object recognition; Production methods; Segmentation; Segments; Thickness; Three dimensional models; Three dimensional printing; Volume segmentation; 3D-printing; Volume segmentation; Multi-material fabrication
• ISSN: 0097-8493; 1873-7684
• DOI: 10.1016/j.cag.2021.07.020

•An efficient radial-basis-function guided segmentation method is proposed to generate smooth and contiguous model partition based on surface attributes, which serves as the initial segmentation result.•A differential evolution based smoothing algorithm is introduced to optimize the cut interfaces of segmented parts constrained by the prescribed minimal printing thickness.•A refinement method for part extractability is designed to detect the infeasible segmented parts and compute division planes to further sub-divide them to ensure the extractability of all split parts.•The proposed technique is applied on a variety of models, and the experimental results shows its advantages over prior methods. Additionally, printed physical objects are provided as a proof of its reliability on current mainstream printers.
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Volume segmentation based on surface attributes is an essential problem in multi-material fabrication and model packing. In practice, current mainstream fabrication techniques have difficulties in yielding models with diverse surface attributes in one pass owing to their craft limitations, making model segmentation a sensible choice for model realization. Partitioning 3D objects into single-attribute volumetric parts prevents fabricating models with different material in a single printing procedure, whereas the arisen challenge is to determine a reliable segmentation solution that is able to handle complicated models in various use scenarios. To achieve this goal, we propose a novel volume partition algorithm generating feasible volumetric parts, each of which is affiliated with one single surface attribute. Our technique enables model segmentation with least conflict and constrained wall thickness so that each volumetric segment can be realized independently by 3D-printing. Generally, it starts with computing a partition proposal guided by radial-based-function iso-surface, then optimizes segmentation interface with a prescribed minimal printing thickness to produce high-quality surface for every volumetric part, and finally splits unextractable volumetric parts into smaller sub-volumes to ensure assemblability of the whole model. As previous methods do not work well in optimizing segment interface for printing, we propose a differential evolution based smoothing algorithm to generate smooth and continuous interface, declining the risk of collision between adjacent volumetric parts. Extensive experimental results are provided in this paper to demonstrate the effectiveness and quality of our proposed technique, showing its advantages on model manufacture over prior methods.