This paper describes novel and fast, simple and robust algorithm with O(N) expected complexity which enables to decrease run-time needed to find an exact maximum distance of two points in E2. The proposed algorithm has been evaluated experimentally on larger different datasets. The proposed algorithm gives a significant speed-up to applications, when medium and large data sets are processed. It is over 10 000 times faster than the standard algorithm for 10^6 points randomly distributed points in E2. Experiments proved the advantages of the proposed algorithm over the standard algorithm and convex hull diameters approaches.
翻译:本文描述了具有O(N)预期复杂性的新颖、快速、简单和稳健的算法,这种算法能够减少在E2中找到两个点的准确最大距离所需的运行时间。提议的算法在较大的不同数据集上进行了实验性评价。提议的算法在处理中大数据集时使应用速度大大加快。它比在E2中随机分布的10 ⁇ 6点的标准算法速度快10 000倍以上。实验证明,提议的算法比标准算法和convex船体直径方法更有利。