Computer vision is a subfield of engineering that designs hardware and software for industrial applications such as quality control and product counting. It automates tedious jobs, allowing human employees to fill more interesting positions. Machine vision systems consist of sensors, cameras, lighting, CPUs, image processing software, and I/O systems. They automate the grading or inspection of thousands of products every day, saving millions of man hours.
Computer vision is an interdisciplinary subfield of engineering. It has to do with the design of the hardware and software needed for a computer vision system with useful industrial applications. The most frequent applications are quality control and product counting. As computer vision advances as a field, it automates some of the more tedious industrial jobs, allowing human employees to fill more interesting positions.
Computer vision is considered a subfield of computer vision in general, which includes neurocomputational investigations of human vision and the development of flexible vision systems for autonomous robotics. The “artificial vision” has the connotation of the application in the industrial field. Computer vision is used in any industrial environment with a significant degree of automation, where product specifications are well defined and products are mass-produced. This includes the automotive industry, the semiconductor industry and the electronics industry in general. Sometimes, a machine vision system is coupled to a robotic arm that discards defective products or even actively participates in the manufacturing of the product.
A machine vision system typically consists of an optical or pressure sensor, a camera, a lighting system, a central processing unit (CPU), associated image processing software, and an I/O system to connect to a larger network. If a machine vision system is located adjacent to a conveyor belt, as is often the case, the sequence of events looks like this: a pressure or optical sensor is triggered when the product moves in front of the camera, a light pulse is triggered to illuminate the target, the camera takes an exposure and the image is processed and fed to a decision tree, which returns an output that is then triggered by an automatic element or displayed to human operators. This simple process can automate the grading or inspection of thousands of products every day, saving millions of man hours.
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