Machine vision systems refer to systems that use computers to perform human visual functions, that is, to use computers to recognize the objective three-dimensional world. Three-dimensional understanding refers to the understanding of the shape, size, distance from the observation point, texture, and motion characteristics (direction and speed) of the observed object.
The input devices for a robot vision system can be cameras, rotating drums, etc., all of which take three-dimensional images as input sources. That is, what is input into the computer is a two-dimensional projection of the three-dimensional visual world. If we consider the transformation from the three-dimensional objective world to a two-dimensional projected image as a forward transformation, then what the machine vision system needs to do is to perform an inverse transformation from this two-dimensional projected image to the three-dimensional objective world, that is, to reconstruct the three-dimensional objective world based on this two-dimensional projected image.
A machine vision system mainly consists of three parts: image acquisition, image processing and analysis, and output or display.
Nearly 80% of industrial vision systems are primarily used for inspection, including improving production efficiency, controlling product quality during production, and collecting product data. Product classification and selection are also integrated into inspection functions. The following example of a single-camera vision system used on a production line illustrates the system's composition and functions.
The vision system inspects products on the production line, determines whether they meet quality requirements, and generates corresponding signals to input into the host computer based on the results. Image acquisition equipment includes light sources, cameras, etc.; image processing equipment includes corresponding software and hardware systems; output devices are related systems connected to the manufacturing process, including process controllers and alarm devices. Data is transmitted to the computer for analysis and product control. If a non-conforming product is detected, an alarm is triggered, and the product is removed from the production line. The results of machine vision are the source of quality information for the CAQ system and can also be integrated with other CIMS systems.
