基于轮廓角点检测的螺纹关键参数视觉测量方法

为解决现有螺纹关键参数视觉测量方法中易存在螺纹角点误检和漏检导致测量精度降低的问题，本文提出一种基于轮廓角点检测的视觉测量方法。首先，使用双边滤波和迭代阈值法改进Canny算子，提高边缘检测的精度；其次，使用双阈值DP算法和Hough变换对轮廓进行分段拟合，在保护边缘的前提下平滑轮廓，并在此基础上使用CTAR算法提取螺纹牙顶、牙底的角点；最后，根据角点的位置信息实现螺纹大径、小径的测量。实验结果表明，相对于现有使用Canny算子和Harris角点检测的视觉测量方法，该方法能准确可靠地检测螺纹的边缘和角点，实现螺纹参数的高精度测量，螺纹大径、小径的平均测量精度分别达到0.003 3 mm和0.002 6 mm。

Visual measurement method of thread key parametersbased on contour corner detection

In order to solve the problem of low accuracy caused by false and missed detection in the corner detection methods of currentvisual measurement of thread key parameters, we proposed a new method based on contour corner detection. Firstly, bilateral filteringand iterative threshold method are used to improve the Canny operator to increase the accuracy of edge detection. Secondly, the doublethreshold DP algorithm and Hough transform were used for piecewise fitting; the edges are protected and Contour smoothness is kept.Furthermore, the corner points of the tip and bottom of threads were extracted with CTAR algorithm. Finally, thread major diameter andminor diameter is measured according to the position information of corner points. Experimental results show that, compared with thetraditional Canny operator and Harris corner detection method, our new method can accurately and reliably detect the thread edges andcorners. Therefore, the high precision measurement of screw thread parameters is realized. The average measurement accuracy of majorand minor diameters of screw thread is 0. 003 3 mm and 0. 002 6 mm, respectively.