DocumentCode :
145189
Title :
The generation algorithm for spherical full-feature Voronoi diagram
Author :
Fengqi Zhang ; Jiatian Li ; Hai Zhao ; Shun Kang ; Xiaojuan Li
Author_Institution :
Inst. of Land Resource Eng., Univ. of Sci. & Technol., Kunming, China
Volume :
1
fYear :
2014
fDate :
26-28 April 2014
Firstpage :
351
Lastpage :
355
Abstract :
As a basic structure of computational geometry, Voronoi Diagram is important to data analysis of GIS. Considering the limitations of traditional vectorial and raster generation algorithm of Voronoi diagram, this paper proposes a spherical Full-Feature Voronoi diagram generation algorithm based on vector data. Through the design of an integrated perspective projection model, data and its connected relationship on the surface of a sphere will be projected to the Euclidean plane. And the discrete feature sets on this Euclidean plane will become point sets for generating sub-Voronoi diagrams. Then these sub-Voronoi diagrams will be merged if they belong to the same feature to accomplish the generation of spherical full-feature Voronoi Diagram. The result of empirical experiment shows that this algorithm is viable, and the accuracy of this algorithm has been discussed at the end of the paper.
Keywords :
computational geometry; data analysis; geographic information systems; GIS; computational geometry; data analysis; discrete feature sets; generating subVoronoi diagram; integrated perspective projection model; raster generation algorithm; spherical full-feature Voronoi diagram generation algorithm; vector data; vectorial generation algorithm; Algorithm design and analysis; Data models; Equations; Heuristic algorithms; Mathematical model; Time complexity; Vectors; Full-feature; Perspective projection; Vector method; Voronoi Diagram;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science, Electronics and Electrical Engineering (ISEEE), 2014 International Conference on
Conference_Location :
Sapporo
Print_ISBN :
978-1-4799-3196-5
Type :
conf
DOI :
10.1109/InfoSEEE.2014.6948130
Filename :
6948130
Link To Document :
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