Machine vision is a technology that enables automatic inspection and analysis for applications including automatic inspection, process control, and robotic guidance by using image processing. It’s important to know that when mentioning machine vision it can be in reference to many different technologies, software and hardware products, integrated systems, actions, methods, and expertise. Machine vision is a technical capability that is integrated with existing technologies in new ways and applies it with the aim to solve real-world problems.
Machine vision is a systems engineering discipline and can be considered distinct from computer vision which is a form of computer science and not done through a tangible piece of hardware such as a vision box or camera attached to a robot. Machine vision is the body of a system and computer vision is the intelligence of the system, similar to how a computer is a frame for what goes inside such as the computer chips that power up the computer.
Without computer vision, machine vision can’t work as it’s the brains behind processing the information. It’s important to note that when computer vision technology advances it increases the possibility of potential applications for machine vision increases respectively. ClearView Imaging makes the valid point that computer vision can process images that might not be photos or videos and instead be an image from a thermal or infrared sensor, a motion detector, or other sources.
Machine vision systems have been in operation since the 1950s and it was between 1980 to 1990 where the technology really started to take off and grow in popularity.
Machine vision is becoming increasingly popular within industrial automation environments while also becoming more frequently used in other industries such as security, autonomous vehicles, food production, packaging, and logistics while also being included in robots and drones. Machine vision can be integrated with technologies such as deep learning and machine learning to help businesses using the technology to understand data better and optimise the business for higher efficiency with an example being how BMW uses the technology alongside AI and machine learning to increase efficiency.
