Recognizing geometric primitives in 3D point clouds of mechanical CAD objects. (April 2023)

• Record Type: Journal Article
• Authors: Romanengo, Chiara; Raffo, Andrea; Biasotti, Silvia; Falcidieno, Bianca
• Is Part Of: Computer aided design. Volume 157(2023)
• Publication Date: 2023-04
• Subjects: Geometric primitives -- Point clouds -- Mechanical CAD objects -- Hough transform; Computer-aided design -- Periodicals; Engineering design -- Data processing -- Periodicals; Computer graphics -- Periodicals; Conception technique -- Informatique -- Périodiques; Infographie -- Périodiques; Computer graphics; Engineering design -- Data processing; Periodicals; Electronic journals; 620.00420285
• DOI: 10.1016/j.cad.2023.103479
• Languages: English
• ISSNs: 0010-4485

Abstract

Abstract: The problem faced in this paper concerns the recognition of simple and complex geometric primitives in point clouds resulting from scans of mechanical CAD objects. A large number of points, the presence of noise, outliers, missing or redundant parts and uneven distribution are the main problems to be addressed to meet this need. In this article we propose a solution, based on the Hough transform, that can recognize simple and complex geometric primitives and is robust to noise, outliers, and missing parts. Additionally, we can extract a series of geometric descriptors that uniquely characterize a primitive and, based on them, aggregate the output into maximal or compound primitives, thus reducing oversegmentation. The results presented in the paper demonstrate the robustness of the method and its competitiveness with respect to other solutions proposed in the literature. Highlights: Recognition of simple and complex geometric primitives on point clouds. Introduction of the Hough transform technique for complex geometric primitives. Recognition of maximal and compound geometric primitives. Extraction of geometric descriptors for characterizing geometric primitives.