3DCCOM Polygon Reduction Algorithm in Presence of Obstacles, Facilators and Constrains

Clustering of spatial data in the presence of obstacles, facilitator and constraints has the very strong practical value, and becomes to an important research issue. Most of the existing spatial clustering algorithm in presence of obstacles and constraints can’t cluster with irregular obstacles. In this paper a 3DCCOM Polygon Reduction Algorithm is proposed. The advantage of this clustering algorithm is to reduce polygon edges, memory would be very less than the matrix approach contains reduction line .We are here going to use Set of reduction lines than matrix approach. Further with help of Polygon Reduction Algorithm, A novel 3DCCOM (3 Dimensional Clustering with Constraints and Obstacle Modeling) algorithm is proposed. 3DCCOM takes into account the problem of clustering in the presence of physical obstacles while modeling the obstacles by Reentrant Polygon Reduction Algorithm. The 3DCCOM algorithm processes arbitrary shape obstacle and finds arbitrary shape clusters efficiently. Meanwhile, the 3DCCOM algorithm used to reduce the complexity of clustering in presence of obstacles, facilators and constraints and the operation efficiency of algorithm is improved. The results of experiment show that 3DCCOM algorithm can process spatial clustering in presence of obstacles, facilitator and constraints and has higher clustering quality and better performance.