A methodology for smoothing of point cloud data based on anisotropic heat conduction theory

• Published in: International journal of advanced manufacturing technology Vol. 30; no. 1-2; pp. 70 - 75
• Main Authors: Zhang, Xue-Chang, Xi, Jun-Tong, Yan, Jun-Qi
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer Nature B.V 01.08.2006
• Subjects: Anisotropy; Conduction heating; Conductive heat transfer; Consultants; Data smoothing; Free form; Heat; Inspection; Motorcycles; Post-processing; Product development; Rapid prototyping; Reverse engineering; Surface geometry; Temperature distribution; Three dimensional models
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-005-0050-9

It is necessary to smooth point cloud data in reverse engineering or the inspection of free-form surfaces because noisy points will have a negative influence on the post-processing of this data. The big problem in smoothing point cloud data is how to solve the dilemma between removing noisy points and keeping feature boundary information, whilst controlling the diffusiveness of noisy points. In this paper, the theory of anisotropic heat conduction is adopted to establish a mathematical model of point cloud data smoothing. The point cloud data can be considered as a temperature field with an adiabatic boundary. So the heat is only conducted inside the temperature filed and has no effect on the outer side. For point cloud data, it means that the smoothing is only on the local area, which makes a good balance between deleting noisy points and keeping feature boundary information. The method has been implemented by using two cases for practical application, and the result proves its efficiency.