Automatic visual inspection based on trajectory data
Automatic inspection tasks have successfully been implemented in several industrial fields and are of growing importance. Visual inspection using optical sensors is wide spread due to the vast variety of different sensors, observable features and comparatively low prices. It seems obvious that corresponding systems are blind towards mechanical features and inspection of those typically requires highly specialized, inflexible and costly systems. Recently, we have shown in the context of sensor-based sorting that tracking objects over a time period allows deriving motion-based features which potentially enable discrimination of optically identical objects, although an optical sensor is used. In this paper, we take one step back from the specific application and study the classification of test objects based on their trajectories. The objects are observed while receiving a certain impulse. We further refrain from manually designing features but use raw coordinates as extracted from a series of images. The success of the method is demonstrated by discriminating spheres made of similar plastic types while bouncing off a plane.