New Quadtree Scheme Using Macro Set

Abstract

In computer applications such as computer–aided part manufacturing and object collision detection, quadtree is a popular representation for object description. However, the space occupied by an object quadtree is known to be rather sensitive to quadtree position. The same object may have different shapes at different positions, and thus different storage sizes. This study proposes a new quadtree scheme using macro set to solve the above problem. This scheme requires no extra memory to store the extra split nodes. Thus the scheme presented here is better than the quadtree in terms of node space saving.