Title: Surface reconstruction algorithm based on local data features

Authors: Kun Zhang; Shiquan Qiao; Kai Gao

Addresses: School of Information Science and Engineering, Hebei University of Science and Technology, Hebei 050018, China ' School of Information Science and Engineering, Hebei University of Science and Technology, Hebei 050018, China ' School of Information Science and Engineering, Hebei University of Science and Technology, Hebei 050018, China

Abstract: With the development of reverse engineering device, the point cloud data, as a common and important form, is applied to the surface reconstruction domain. Since the point data is so large, scattered and unordered, the representation of point cloud and surface reconstruction is critical contents in reverse engineering system. In this paper, we redefine the representation of point cloud based on set theory, and derive the rules of neighbour relationship of data. Then, we adopt the KD-tree algorithm and improve its searching approach. In addition, the GeoSurface algorithm is proposed, which uses iterative strategy to mesh surface and uses the depth of KD-tree to control the parameters. Finally, we verify the GeoSurface algorithm. The experimental results show the GeoSurface algorithm is effective, and achieves better results in running time and quality of surface reconstruction compared with greedy and Poisson reconstruction algorithm.

Keywords: point cloud; geometrical features; set theory; surface reconstruction; reverse engineering.

DOI: 10.1504/IJMIC.2018.095336

International Journal of Modelling, Identification and Control, 2018 Vol.30 No.3, pp.197 - 205

Received: 24 Feb 2017
Accepted: 02 Oct 2017

Published online: 17 Sep 2018 *

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