A wide range of single-purpose point sensors such as proximity sensors, lasers and photocells have long played a key role in virtually all factory automation systems by detecting the presence of parts or assemblies, performing measurements, and identifying colors. Machine vision systems, on the other hand, perform more complicated operations such as complete inspection of a part. The operations performed by machine vision may include multiple dimensions and presence or absence of various components or determining the position and orientation of a component for a subsequent operation. More recently, simpler, less expensive machine vision sensors have emerged to target operations that are currently performed by point sensors as well as many other operations at a price that is in the same ballpark.
For many years, developers of automated systems have used traditional point sensors to detect the presence or absence of parts or assemblies for controlling machines and processes. For example, photoelectric sensors generate a beam of light that is typically aimed at a detector. At some point in the process, the part is expected to make an appearance at just the right position to interrupt the light circuit. The sensor provides a binary output depending on the presence or absence of light at the detector. Point sensors are still relevant in applications where the mere verification of the presence or absence of a part is all that is required. But the capabilities of photocells are limited; by limiting the inspection to a single point, photocells have no way of knowing if the part is the one that was expected, nor can they assess the quality of the part or whether the part has been correctly assembled.