Surface reconstruction algorithm based on local data features Online publication date: Wed, 03-Oct-2018
by Kun Zhang; Shiquan Qiao; Kai Gao
International Journal of Modelling, Identification and Control (IJMIC), Vol. 30, No. 3, 2018
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook