Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00170-005-0027-8
Title: Triangular mesh generation employing a boundary expansion technique
Authors: Shi, M. 
Zhang, Y.F. 
Loh, H.T. 
Bradley, C.
Wong, Y.S. 
Keywords: Error-based cloud data reduction data modelling
Reverse engineering
Triangulation
Issue Date: Aug-2006
Source: Shi, M., Zhang, Y.F., Loh, H.T., Bradley, C., Wong, Y.S. (2006-08). Triangular mesh generation employing a boundary expansion technique. International Journal of Advanced Manufacturing Technology 30 (1-2) : 54-60. ScholarBank@NUS Repository. https://doi.org/10.1007/s00170-005-0027-8
Abstract: This paper presents a triangulation method for modelling very large sets of cloud data. The three-dimensional (3D) data sets are produced by a machine vision system and/or coordinate measuring machine (CMM). The algorithm is suitable for processing the data collected from objects composed of free form surface patches especially with interior holes. This is accomplished from the 3D data sets in two steps. Firstly, the original cloud data is reduced into a simplified data set employing a data reduction technique (voxel binning method), in which the error between the cloud data and the meshed surface is used to control the data reduction. Secondly, the triangulation process starts with a randomly selected seed triangle. The triangular mesh extends outward by continuously linking suitable external points to it along the boundary edges of the meshed area. A complex free form surface with interior holes can be triangulated in one computing session without manually dividing it into several simple patches. The error-based data reduction parameters are extracted from the cloud data set, by a series of local surface patches, and the required spatial error between the final triangulation and the cloud data. Experimental results are given to illustrate the efficacy of the technique for rapidly constructing a geometric model from 3D digitised cloud data.
Source Title: International Journal of Advanced Manufacturing Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/61621
ISSN: 02683768
DOI: 10.1007/s00170-005-0027-8
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

6
checked on Dec 7, 2017

WEB OF SCIENCETM
Citations

6
checked on Nov 22, 2017

Page view(s)

36
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.