Line Detection for Point Set of Varying Discrete Degrees

Haidong Yuan, Huadong Ma
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引用次数: 3

Abstract

Many line detection algorithms based on Hough transform are used to work on continuous set of points, such as edge image, which is composed of continuous or almost continuous points. When these algorithms work on the high-discrete point set, they produce the multi-short-line segments because of the noise and large gaps between points, which seldom characterize the whole line segment completely. We proposed an improved HoughLines algorithm to solve this problem: First, we propose a new sorting strategy of the point coordinates that is self-adaptive for each line segment; second, we improve the strategy of finding the non-background points that contributed to peaks of Hough transform matrix through a tolerance threshold. The improved algorithm can detect line segments in point set of varying discrete degrees at a high precision. A number of experiments show our method is very efficient.
变离散度点集的直线检测
许多基于霍夫变换的线检测算法都是用来检测连续的点集,如边缘图像,它是由连续或几乎连续的点组成的。当这些算法在高度离散的点集上工作时,由于噪声和点之间的大间隙会产生多个短线段,无法完全表征整个线段。我们提出了一种改进的HoughLines算法来解决这个问题:首先,我们提出了一种新的点坐标排序策略,该策略对每个线段都是自适应的;其次,改进了通过容差阈值寻找霍夫变换矩阵峰的非背景点的策略;改进后的算法可以在不同离散度的点集中以较高的精度检测线段。大量的实验表明我们的方法是非常有效的。
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