A robustness-enhancing method for real-time surface defection inspection

摘要

Surface defection inspection methods based on machine vision have lots of advantages over many other automatic inspection methods, such as higher flexibility, lower overall cost, etc. However, the robustness of these methods is still unsatisfactory. Inspection of magnetic rings which are rich in texture and have various defections is a typical machine-vision-based inspection task with high difficulty. Therefore, conclusions of the research on this problem are representative. In this paper, factors which lead to the variation of the inspection results are classified, and then a quantitative analysis for inspection systems introducing a new concept of robustness index is proposed. As an approach for enhancing robustness, the effect of the algorithm rule is focused on. The author extracts defection features on three levels in designing the rule and come to a conclusion that a complete extraction on higher level can enhance the robustness of the system after theory analysis and experiments.