Accelerating Polygon Clipping

Abstract

Polygon clipping is a central part of image generation and image visualization systems. In spite of its algorithmic simplicity it consumes a considerable amount of hardware or software resources. Polygon clipping performance is dominated by two processes: intersection calculations and data transfers. The paper analyzes the prevalent Sutherland-Hodgman algorithm for polygon clipping and identifies cases for which this algorithm performs inefficiently. Such cases are characterized by subsequent vertices in the input polygon that share a common region, e. g. a common 'halfspace. The paper will present new techniques that detect such constellations and simplify the input polygon such that the Sutherland-Hodgman algorithm runs more efficiently. Block diagrams and pseudo-code demonstrate that the new techniques are well suited for both hardware and software implementations. Finally, the paper discusses the results of a prototype implementation of the presented techniques. The analysis compares the performance of the new techniques to the traditional Sutherland-Hodgman algorithm for different test scenes. The new techniques reduce the number data transfers by up to 90 % and the number of intersection calculations by up to 60 %.