渐进式概率霍夫变换用于线路检测

C. Galambos, J. Kittler, Jiri Matas
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引用次数: 193

摘要

我们提出了一种新的霍夫变换算法,称为渐进概率霍夫变换(PPHT)。与概率HT不同的是,标准HT是在预先选择的部分输入点上执行的,PPHT通过利用差异和选票的比例来检测具有不同数量支撑点的可靠线,从而最大限度地减少了检测线所需的计算量。用于投票的分数不需要特别指定或使用先验知识,如在概率HT中;它是输入数据固有复杂性的函数。该算法非常适合具有固定可用处理时间的实时应用程序,因为投票和线路检测是交错的。最显著的特征可能首先被发现。实验表明,在许多情况下,PPHT比标准HT有优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Progressive probabilistic Hough transform for line detection
We present a novel Hough Transform algorithm referred to as Progressive Probabilistic Hough Transform (PPHT). Unlike the Probabilistic HT where Standard HT is performed on a pre-selected fraction of input points, PPHT minimises the amount of computation needed to detect lines by exploiting the difference an the fraction of votes needed to detect reliably lines with different numbers of supporting points. The fraction of points used for voting need not be specified ad hoc or using a priori knowledge, as in the probabilistic HT; it is a function of the inherent complexity of the input data. The algorithm is ideally suited for real-time applications with a fixed amount of available processing time, since voting and line detection is interleaved. The most salient features are likely to be detected first. Experiments show that in many circumstances PPHT has advantages over the Standard HT.
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