Output-Sensitive Parallel Algorithm for Polygon Clipping

S. Puri, S. Prasad
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引用次数: 15

Abstract

Polygon clipping is one of the complex operations in computational geometry. It is a primitive operation in many fields such as Geographic Information Systems (GIS), Computer Graphics and VLSI CAD. Sequential algorithms for this problem are in abundance in literature but there are very few parallel algorithms solving it in its most general form. We present the first output-sensitive CREW PRAM algorithm, which can perform polygon clipping in O(logn) time using (n + k + k') processors, where n is the number of vertices, k is the number of edge intersections and k' is the additional temporary vertices introduced due to the partitioning of polygons. The current best algorithm by Karinthi, Srinivas, and Almasi [1] does not handle self-intersecting polygons, is not output-sensitive and must employ ⊝(n2) processors to achieve O(logn) time. Our algorithm is developed from the first principles and it is superior to [1] in cost. It yields a practical implementation on multicores and demonstrates 30x speedup for real-world dataset. Our algorithm can perform the typical clipping operations including intersection, union, and difference.
多边形裁剪的输出敏感并行算法
多边形裁剪是计算几何中较为复杂的运算之一。它是地理信息系统(GIS)、计算机图形学和VLSI CAD等许多领域的基本操作。对于这一问题的顺序算法在文献中有很多,但很少有并行算法在其最一般的形式下解决它。我们提出了第一个输出敏感的CREW PRAM算法,该算法可以使用(n + k + k')处理器在O(logn)时间内执行多边形裁剪,其中n是顶点的数量,k是边缘相交的数量,k'是由于多边形划分而引入的额外临时顶点。Karinthi, Srinivas和Almasi[1]目前最好的算法不处理自相交多边形,对输出不敏感,必须使用⊝(n2)处理器来实现O(logn)时间。我们的算法是由第一原理发展而来的,在成本上优于[1]。它产生了一个在多核上的实际实现,并演示了真实数据集的30倍加速。我们的算法可以完成典型的裁剪操作,包括交、并、差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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