A fast and efficient method for solving the multiple line detection problem

R. Scitovski, Una Radojicic, K. Sabo
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引用次数: 3

Abstract

In this paper, we consider the multiple line detection problem on the basis of a data points set coming from a number of lines not known in advance. A new and efficient method is proposed, which is based upon center-based clustering, and it solves this problem quickly and precisely. The method has been tested on 100 randomly generated data sets. In comparison to the incremental algorithm, the method gives significantly better results. Also, in order to identify a partition with the most appropriate number of clusters, a new index has been proposed for the case of a cluster whose lines are cluster-centers. The index can also be generalized for other geometrical objects.
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一种快速有效的多线检测方法
在本文中,我们考虑了多线检测问题的基础上的数据点集来自一些事先未知的行。提出了一种新的基于中心聚类的高效聚类方法,能够快速准确地解决这一问题。该方法已在100个随机生成的数据集上进行了测试。与增量算法相比,该方法的效果明显更好。此外,为了识别具有最适当簇数的分区,还提出了一种新的索引,用于线为簇中心的簇的情况。该指标也可推广到其他几何对象。
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