So, a vision system would have to check the quality of the milled and polished surface, and check for the presence of holes with the proper threads. After visiting the auto manufacturer to study the machining problem, DS engineers set up a prototype inspection system in their lab and inspected an oil pan under various lighting conditions. The experiments showed that two images, each taken under different lighting conditions, would let the system properly determine the quality of the operations that the robotic system performed on the oil pans. So we decided on strong bright-field illumination to brighten the surface. On the other hand, to detect unmilled surfaces we needed light that would emphasize bumps on the surface.
Oblique lighting does that.
The light reflects directly into the camera and lets the image show if the hole is bored, beveled, and threaded. If light reflects from where the software expects to find a hole, the system rejects the part because holes will not reflect light. The software measures the maximum diameter of the holes and determines gray-level features and a gradient that measures how quickly light levels change. The software can tell when the robotic machine has or has not cut threads because reflections from threads create high gradients. An image from the hole-inspection step shows two holes of proper diameter, with the proper threads.