Eliminating False Positives of Hough Transform with Constructive Testing in Line Detection

Bing-Yun Wang, Yi-Chun Yen, Y. Cheng
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Abstract

Routines for Hough transform for line detection use multiple parameters that can be difficult to determine sometimes. Even when a good deal of effort is spent on determining these pa-rameters, the true positives found are often accompanied by some false positives. In this paper, we propose a method called constructive testing for post-processing the lines returned by Hough transform routines with the objective to eliminate false positives. Given a detected line, constructive testing builds a small set of parallel lines based on it. Then, the detected line's distinctiveness as a line in contrast to the other constructed par-allel lines is computed with sample statistics. The detected lines are accepted or rejected based on their distinctiveness. Experimental results show determining a threshold of distinc-tiveness is intuitive and easy and that it effectively eliminates a large number of false positives.
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线路检测中利用建设性检测消除霍夫变换的假阳性
用于线检测的霍夫变换例程使用多个参数,有时难以确定。即使花费了大量的精力来确定这些参数,发现的真阳性常常伴随着一些假阳性。在本文中,我们提出了一种称为建设性测试的方法,用于后处理霍夫变换例程返回的行,目的是消除误报。给定一条检测到的线,建设性测试在此基础上构建一组平行线。然后,利用样本统计量计算检测到的直线相对于其他构造的平行线的显著性。检测到的线条根据其独特性被接受或拒绝。实验结果表明,确定显著性阈值直观、简便,能有效地消除大量误报。
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