基于机器视觉的膨胀阀安装孔缺陷检测方法

针对工业生产中膨胀阀安装孔缺陷自动检测的需求，提出一种基于机器视觉的安装孔缺陷检测方法。使用SURF特征匹配定位待检测区域，利用双阈值迟滞分割法去除噪声；通过Canny算子计算轮廓边缘，利用邻域生长法提取轮廓信息。为克服缺陷信息的干扰，准确定位安装孔圆心，提出基于几何矩与最小二乘拟合的圆心定位方法。根据轮廓上的点到圆心的距离分割出缺陷轮廓并在输入图像上进行标注，从而实现安装孔缺陷的检测。结果表明：所提出的算法能准确检测膨胀阀安装孔的缺陷，满足工业生产中自动检测的需求。

Defect Detection Method of Expansion Valve Mounting Hole Based on Machine Vision

In order to realize the automatic detection of the defects in the expansion valve mounting hole in industrial production,a defect defection method for expansion valve mounting hole was proposed based on machine vision.SURF feature matching was used to locate the region of interesting (ROI),and dual threshold hysteresis segmentation method was used to eliminate the noise;the contour edges were calculated by using the Canny operator,and the contour information was extracted by using the neighborhood growth method.In order to overcome the interference of defect information and accurately locate the center of valve hole,a method of circle center location based on geometric moment and least square fitting was proposed.According to the distance from the point on the contour to the center of the circle,the defect contour was segmented and marked on the input image,so the detection of defects was realized.The results show that by using the proposed algorithm,the defects of the expansion valve mounting hole can be accurately detected and the requirements of automatic detection in industrial production can be met.