基于图像处理的胶管缺陷在线检测系统开发

为实现胶管表面缺陷的在线检测，提出了一种基于图像处理技术的检测方法.采用图像剪切方法选中胶管区域，利用中值滤波和Canny边缘提取处理图像，清除与图像边界连接区，避免胶管边界的干扰，使用形态学膨胀方法对缺陷区域图像分割，根据缺陷特征完成缺陷分类.采用三台CMOS相机环胶管圆周布置，间隔120°，光源采用同轴光源.基架结构具有调节功能，保证胶管在三台相机的中心位置.通过检测系统在车间生产线上试用，测试结果表明缺陷检测正确率在96%以上，可实现胶管表面缺陷自动检测和及时报警. 

A On-Line Detection System Development Based on Image Processing for Rubber Hose Defects

A method based on image processing was proposed to realize an online detection of rubber hose surface defects. An image shear method was taken to select hose area. The median filter and Canny edge detection were used to extract graph. To avoid the boundary influence in separating the defects from the hose, a morphological expansion method was used for the defect area separation. According to the character of defects, the defects were classified. Three CMOS cameras within the same plane were layout around the hose axis, interval of 120°. Coaxial light source was used to improve the brightness of hose surface. The mechanical platform of the detection system could adjust the cameras in three directions to ensure the hose in the center position. This system was tested in the hose workshop of Codan-Lingyun Automotive Rubber Hose Co Ltd. The experiment results show that the correct rate of detection is over 96 percent and it can detect the hose surface defects automatically and alarm timely.