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Computer vision has more flexibility in this regard as it can work by using real-life images or synthetic images. Unlike machine vision systems, computer vision systems do not require a camera. Computer vision systems can interpret data from a saved image and produce a result or set of results. In addition, computer vision does not necessarily need to capture an image as it can work off of saved images.

On the other hand, computer vision systems can be used on their own. In other words, machine vision needs to be part of a larger machine system. Machine vision systems also typically contain a camera, lens, processor, and software to enable the machine to make these decisions. These decisions can include pass or fail decisions in a production line that are based on a defect that the vision system detected. Machine vision systems capture images using digital cameras and then process them to output a decision. While both machine vision and computer vision involve ingesting and analyzing visual inputs, there are differences between the two. What are the Main Differences between Machine Vision and Computer Vision? The image analysis is done by the machine vision system, which can be applied across a wide range of theoretical and practical applications. On the other hand, computer vision refers to the capture and automation of image analysis. Machine vision systems involve image processing and work on a set of rules and parameters to support manufacturing applications such as quality assurance. One difference between computer vision and machine vision is that machine vision systems give vision capability to existing technologies. Both machine vision and computer vision can perform tasks with a faster speed than ordinary human vision, but there are some key differences between the two.

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