Proceedings of the 2017 6th International Conference on Measurement, Instrumentation and Automation (ICMIA 2017)

Automatic recognition method of doors and windows fan area based on convex hull algorithm

Authors
Kai Dong, Xiangbo Ze, Yibing Qu, Han Zhang
Corresponding Author
Kai Dong
Available Online June 2017.
DOI
https://doi.org/10.2991/icmia-17.2017.56How to use a DOI?
Keywords
Plastic windows; fan regions; two-dimensional convex hulls; computational geometry
Abstract
In the computer aided design of doors and windows, the computer only accurate positioning of fan region in the original frame position to further the design of the plastic window. Based on the design software of a door and window, the concept of convex hull in computational geometry is applied to identify the fan regions in the design of plastic steel doors and windows. The convex hull algorithm is used to analyze the frame coordinates to form a convex hull.Using Delaunay triangulation algorithm for convex hull analysis all triangle region The triangulation network is analyzed and merged, and all the fan regions are finally obtained. The convex hull algorithm can overcome the traditional plastic window cannot identify shaped window design software fan area faults, thus greatly expand the scope of design software.
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Proceedings
2017 6th International Conference on Measurement, Instrumentation and Automation (ICMIA 2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-387-6
ISSN
1951-6851
DOI
https://doi.org/10.2991/icmia-17.2017.56How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Kai Dong
AU  - Xiangbo Ze
AU  - Yibing Qu
AU  - Han Zhang
PY  - 2017/06
DA  - 2017/06
TI  - Automatic recognition method of doors and windows fan area based on convex hull algorithm
BT  - 2017 6th International Conference on Measurement, Instrumentation and Automation (ICMIA 2017)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmia-17.2017.56
DO  - https://doi.org/10.2991/icmia-17.2017.56
ID  - Dong2017/06
ER  -