Machine vision is an important component of modern technologies and an effective way to automate various processes, especially in enterprises using computer technology and robotics.
How does machine vision work? Devices located directly on the object transmit data in the form of a photo or video image to a computer, where the received information is processed and any decision is made on further actions or operations. And all this in a fraction of a second – such an “inspection” of the enterprise 24/7.
What is the difference between machine vision and computer vision
Machine vision is often confused with computer vision, replacing these two concepts. Both use image capture and analysis to perform tasks with speed and precision beyond the reach of the human eye, but it’s not entirely correct to think of machine vision and computer vision as synonymous.
Computer vision is a field of computer science that deals with technologies and tools that allow computers to see the same as humans and interpret the world around them. A prime example of the application of computer vision is Tesla electric vehicles : eight cameras provide a 360-degree view around the car at a distance of up to 250 meters.
Information from them enters the computer, which recognizes other cars in the video, “hard” and “soft” objects, road markings, etc., using this information to plot routes and perform maneuvers. Computer vision can analyze not only images, but also graphs, tables and other data.
Machine vision is a piece of computer vision that can be used on its own without having to be part of a larger machine system. But the machine vision system does not work without a computer and special software. Machine vision is most often, but not always, used in manufacturing.
Numbers and trends
According to Grand View Research, the global machine vision market in 2020 was $12.3 billion. The growth rate of this market between 2021 and 2028 is expected to increase by 6.9% annually.
The main driver in this market is the growing demand for quality control and automation in various industries. In addition, the need for visually guided robotic systems in the automotive, pharmaceutical, chemical, and consumer segments is expected to drive market growth.
According to a recent report Association for Advancing Automation in the first half of 2021, the robot and vision markets grew by 18% (nearly $1.5 billion) compared to the same period in 2020.
Machine vision application examples
To better understand how machine vision works, here are a few specific examples of the application of this technology.
During the COVID-19 pandemic, the Russian startup Addreality trained an algorithm to detect the presence of a medical mask on a person’s face, as well as count the number of people entering the room. This technology has become relevant for organizations that work with a large number of people every day.
Is the future already here?
Machine vision can be widely applied. This technology helps to automate routine processes in many industries, making them comfortable and safe for people.
For example, many airports around the world are starting to introduce contactless technologies with a face recognition system. So, at the international airport of Hong Kong at the border crossings there are biometric kiosks with a face recognition system. They allow travelers to cross the border in seven seconds. Such a system, among other things, is more hygienic than, for example, using fingerprint biometrics.
A similar technology is being tested at Barcelona Airport. It is integrated into the self-service baggage check-in system. The system uses biometrics and does not require the presentation of identification documents.
