Abstract
AbstractWe present and analyse the Hough transform (HT) to recognise and approximate space curves in digital models, a problem that is not currently addressed by the standard HT. Our method works on meshes and point clouds and applies to models even incomplete or affected by noise, thus being suitable for the analysis of digital models deriving from 3D scans. In our approach we take advantage of a recent HT formulation for algebraic curves to define both parametric and implicit space curve representations. We also provide a comparative analysis of the HT-based method when dealing with both curve representations, discussing the computational performance and the approximation accuracy of both strategies.
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Geometry and Topology,Computer Vision and Pattern Recognition,Condensed Matter Physics,Modeling and Simulation,Statistics and Probability
Reference27 articles.
1. Araújo, A.M.C., Oliveira, M.M.: A robust statistics approach for plane detection in unorganized point clouds. Pattern Recognit. 100, 107–115 (2020). https://doi.org/10.1016/j.patcog.2019.107115
2. Ballard, D.H.: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognit. 13(2), 111–122 (1981)
3. Beltrametti, M., Sendra, J., Sendra, J., Torrente, M.: Moore–Penrose approach in the Hough transform framework. Appl. Math. Comput. 375, 125083 (2020)
4. Beltrametti, M.C., Robbiano, L.: An algebraic approach to Hough transforms. J. Algebra 37, 669–681 (2012)
5. Cole, F., Golovinskiy, A., Limpaecher, A., Barros, H.S., Finkelstein, A., Funkhouser, T., Rusinkiewicz, S.: Where do people draw lines? ACM Trans. Graph. 27(3), 1–11 (2008)
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献