Title :
Preliminary study on cluster methods for geometric shape based on correlation graph
Author :
Wang, Wei ; Quan, Cong ; He, Jin ; Wang, Xinsheng
Author_Institution :
Fac. of Resources & Environ. Sci., Hubei Univ., Wuhan, China
Abstract :
On study for geographic information science, description and measurement for shape of spatial objects is a very important research subject. But current methods used in this field all have some limitations. In this paper the authors discuss a new method to solve the problem better. The authors also put forward a new association matrix-Angular Matrix, which can represent geometric shape in a better way. Preliminary experiment shows that this method can express characteristics of geometric shape better with desirable calculation efficiency.
Keywords :
computational geometry; geographic information systems; graph theory; matrix algebra; pattern clustering; angular matrix; association matrix; cluster methods; correlation graph; geographic information description; geographic information science; geometric shape; spatial objects; Correlation; Laplace equations; Shape; Shape measurement; Symmetric matrices; Vectors; Angular Matrix; Association Matrix; Clustering Analysis; Delaunay Triangulation Network; Geometric Shape;
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4577-1414-6
DOI :
10.1109/CECNet.2012.6201693
