Ε-maps: Characterizing, detecting and thickening thin features in geometric models. (August 2017)

• Record Type: Journal Article
• Authors: Cabiddu, Daniela; Attene, Marco
• Is Part Of: Computers & graphics. Volume 66(2017)
• Page Start: 143
• Page End: 153
• Publication Date: 2017-08
• Subjects: Thin features -- Thickness computation -- Thickening -- 3D printing; Computer graphics -- Periodicals; 006.6
• DOI: 10.1016/j.cag.2017.05.014
• Languages: English
• ISSNs: 0097-8493

Abstract

Highlights: An innovative mathematical model to characterize thin features. An innovative algorithm to detect thin features in planar and solid objects. Our method is able to detect thin features in the object and in its complementary. A novel approach to thick thin features while leaving the other parts unchanged. Graphical abstract: Abstract: We focus on the analysis of planar shapes and solid objects having thin features and propose a new mathematical model to characterize them. Based on our model, that we call an ϵ-shape, we show how thin parts can be effectively and efficiently detected by an algorithm, and propose a novel approach to thicken these features while leaving all the other parts of the shape unchanged. When compared with state-of-the-art solutions, our proposal proves to be particularly flexible, efficient and stable, and does not require any unintuitive parameter to fine-tune the process. Furthermore, our method is able to detect thin features both in the object and in its complement, thus providing a useful tool to detect thin cavities and narrow channels. We discuss the importance of this kind of analysis in the design of robust structures and in the creation of geometry to be fabricated with modern additive manufacturing technology.