基于渐进概率霍夫变换的工件相干线检测方法

Ziyao Wang, Dali Yang, Qiang Tong
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引用次数: 0

摘要

工件线条的检测与提取是工业生产实践中的基础和关键。为了解决工件线条检测和提取过程中的不连续和断开问题,提出了一种相干线条检测方法,即改进的渐进概率霍夫变换线条检测(PPHT)。改进后的PPHT首先结合原PPHT算法进行边缘检测,寻找工件对象的直线。该方法在剔除噪声线后,通过寻找共线候选者,将检测到的线分成若干组。然后计算每组前景图像的支持像素,并应用最小二乘回归得到最终的直线结果。在本文中,我们对三种不同矩形工件的30幅图像进行了实验。结果表明,与PPHT相比,改进后的PPHT将线性检测准确率p的相对错误率平均降低了62.06%,召回率R的相对错误率平均降低了43.6%,从而显著缓解了PPHT中存在的不连续问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Method of Workpiece Coherent Line Detection Based on Progressive Probabilistic Hough Transform
The detection and extraction of workpiece lines is the basis and key in the industrial production practice. In order to solve the discontinuity and disconnection problem during the line detection and extraction of a workpiece, we propose a coherent line detection method, which is Improved Progressive Probabilistic Hough Transform line detection(PPHT). Improved PPHT first performs edge detection combine with original PPHT algorithm to find lines of workpiece object. After discarding noise lines, this method divide the detected lines into several groups by finding collinear candidates. Then we calculate the supporting pixels of every group with foreground image, and apply Least Square Regression to achieve final line results. In this paper, we performed an experiment on thirty images of three different rectangular workpieces.The results indicate that, comparing to the PPHT, Improved PPHT decreased the relative error rate of the linear detection accuracy p by 62.06% on average, and the relative error rate of the recall rate R has decreased by 43.6% on average, thereby significantly mitigate the discontinuity existing in PPHT.
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