表面物理损伤检测是轴类工件质量检测的重要环节，为提高表面质量检测的自动化水平并建立相关行业标准，设计了一套机器视觉检测系统来实现生产中轴类工件的表面检测。采用黑白线阵CCD相机通过暗视野前向照明方式获取合适的图像；经过图像增强、滤波等预处理后采用最大类间方差法对图像进行阈值分割；经过形态学处理，提取缺陷轮廓信息；以轮廓的长宽比以及面积作为评价准则，提取主要轮廓；计算缺陷重心坐标，即定位点坐标；单片机通过与上位机通信，控制打码笔标记出缺陷的位置。采用该系统在不同轴类工件上进行试验,结果表明：缺陷检测系统误检率在5%以下，漏检率为0，能满足轴类工件表面在线实时检测的要求。

Surface physical damage detection is an important part of the shaft part quality inspection. In order to improve the automation level of the quality detection of shaft part and establish its relevant industry quality standard, a machine vision inspection system connected with MCU was designed to realize the surface detection of shaft part. The system adopted the monochrome line-scan digital camera and used the dark-field and forward illumination technology to acquire images with high contrast; the images were segmented to Bi-value images through maximum between-cluster variance method after image filtering and image enhancing; then the mainly contours were extracted based on the evaluation criterion of the aspect ratio and the area; then the coordinates of the center of gravity of defects area, namely locating point coordinates were calculated. At last, locations of the defects area were marked by the coding pen communicated with MCU. Experiment showed that no defect was omitted and false alarm error rate was lower than 5%, which showed that the designed system met the demand of shaft part on-line real-time detection.