Parallel Algorithms for Image Processing and Computational Geometry

这是连续三年获奖的第一年。 的 研究包括设计、分析和实施 解决图像问题的有效算法和范例 大规模并行的分析和计算几何 电脑 算法开发的重点将放在 细粒度的分布式存储器拓扑， 现有的机器或原型已经存在。 其中包括 网格、超立方体、金字塔和可重构网格。 的 重点将放在机器人学的应用问题上 和图像处理。 首先，以下将是 考虑：2-和3-维问题，在中级 图像分析，以及二维和三维问题， 计算几何 所有问题的最优性 审议了目前在适当的 建筑 此外，对于这些问题， 考虑到，二维对象的算法可以扩展 在最佳时间内解决三维物体的问题。 相反，似乎将采取根本不同的方法， 必需的. 所考虑的问题涉及连通性， 邻近度、面积、交叉点和最小面积包围 多边形，仅举几例。

This is the first year of a 3-year continuing award. The research consists of the design, analysis, and implementation of efficient algorithms and paradigms to solve problems in image analysis and computational geometry on massively parallel computers. The focus of the algorithm development will be on fine-grained distributed memory topologies for which commercially available machines or prototypes already exit. These include the mesh, hypercube, pyramid, and reconfigurable mesh. The concentration will be on problems with application to robotics and image processing. Initially, the following will be considered: 2-and 3-dimensional problems in intermediate-level image analysis, as well as 2- and 3-dimensional problems in computational geometry. The optimality of all of the problems considered ar currently open problems on the appropriate architectures. Further, it does not appear that for the problems considered, algorithms for 2-dimensional objects can be extended to solve the problems for 3-dimensional objects in optimal time. Rather, it appears that radically different approaches will be required. The problems considered involve connectivity, proximity, area, intersection, and minimal-area enclosing polygons, to name a few.