In order to detect boundary points of clusters quickly and efficiently, a boundary points detecting
algorithm(EDGE) is proposed, which employs grid technique and joint entropy. Grid technique is used to search the scope of
grids which the boundary of clusters is located in and joint entropy is used to detect boundary points of clusters in these grids.
The experimental results show that EDGE can detect boundary points of clusters in datasets with noises/outliers effectively
and efficiently.