根据树脂镜片在线检测的要求和疵病尺寸的特点，提出一种基于两级图像采集的视觉在线检测方法。采用两级疵病图像采集系统，提高了图像的采集速度，减少数据量，从而提高图像处理速度。利用图像处理工具进行图像处理，根据疵病的填充度和位置等特征实现对疵病的快速识别，利用两级采集系统的不同精度实现对不同尺寸疵病的测量，根据识别和测量结果实现对镜片的分级。实验表明该方法可以满足镜片在线实时检测的要求，并且有很好的分级效果。

An online machine vision defect detection method based on two-stage image acquisition structures is proposed for the online detection of the hard resin lenses. With the two-stage image acquisition structures, this method is able to increase the image processing speed by improving the image acquisition speed and reducing the image data amount. With the usage of image processing tools, the defects are rapidly identified according to the characteristics of filling degree and position, and the sizes of defects are determined based on the different measurement accuracies of the two-image acquisition stages. Then the lenses are classified according to the obtained identification and sizes. The experimental results show that this method can meet the requirement of online real-time detection for resin lenses and has a good classification result.