Automatic optical inspection of microscale defects on curved surfaces

Abstract

In many areas of manufacturing, there is a growing need for imaging technology that non-destructively inspects the surface of products. However, detecting micro-defects on curved surfaces is challenging because the appropriate imaging conditions can vary depending on the shape of the curved surface. To address this problem, we have developed a method for visualizing micro-defects on curved surfaces that uses an imaging system to obtain a color map of light directions reflected from the surface. This imaging system is equipped with a stripe-patterned multicolor filter and a radially diffusing illumination light. The unique characteristics of this imaging system enable it to capture drastic spatial changes in the direction of light, which are caused by micro-defects on the curved surfaces, as differences in image color. Furthermore, we have also constructed an image-processing algorithm that automatically detects these micro-defects. The key point of this image-processing algorithm is that it automatically detects areas where drastic color changes have occurred due to micro-defects by using spatial frequency filtering techniques. As a result, the developed method was shown to have the ability to automatically detect micro-defects on curved surfaces with depths of several tens of micrometers.

Keywords

• imaging
• optics
• micro-defects
• curved surfaces
• automatic inspection