Editing Computer vision (section)

==Hardware==
[[File:LiDAR_Scanner_and_Back_Camera_of_iPad_Pro_2020_-_3.jpg|thumb|upright|A [[iPad Pro (4th generation)|2020 model iPad Pro]] with a [[LiDAR]] sensor]]

There are many kinds of computer vision systems; however, all of them contain these basic elements: a power source, at least one image acquisition device (camera, ccd, etc.), a processor, and control and communication cables or some kind of wireless interconnection mechanism. In addition, a practical vision system contains software, as well as a display in order to monitor the system. Vision systems for inner spaces, as most industrial ones, contain an illumination system and may be placed in a controlled environment. Furthermore, a completed system includes many accessories, such as camera supports, cables, and connectors.

Most computer vision systems use visible-light cameras passively viewing a scene at frame rates of at most 60 frames per second (usually far slower).

A few computer vision systems use image-acquisition hardware with active illumination or something other than visible light or both, such as [[structured-light 3D scanner]]s, [[thermographic camera]]s, [[hyperspectral imager]]s, [[radar imaging]], [[lidar]] scanners, [[magnetic resonance image]]s, [[side-scan sonar]], [[synthetic aperture sonar]], etc. Such hardware captures "images" that are then processed often using the same computer vision algorithms used to process visible-light images.

While traditional broadcast and consumer video systems operate at a rate of 30 frames per second, advances in [[digital signal processing]] and [[Graphics processing unit|consumer graphics hardware]] has made high-speed image acquisition, processing, and display possible for real-time systems on the order of hundreds to thousands of frames per second. For applications in robotics, fast, real-time video systems are critically important and often can simplify the processing needed for certain algorithms. When combined with a high-speed projector, fast image acquisition allows 3D measurement and feature tracking to be realized.<ref>{{cite book|last1=Kagami|first1=Shingo|title=2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops|chapter=High-speed vision systems and projectors for real-time perception of the world|date=2010|volume=2010|pages=100–107|doi=10.1109/CVPRW.2010.5543776|isbn=978-1-4244-7029-7|s2cid=14111100}}</ref>

[[Egocentric vision]] systems are composed of a wearable camera that automatically take pictures from a first-person perspective.

As of 2016, [[vision processing unit]]s are emerging as a new class of processors to complement CPUs and [[graphics processing units]] (GPUs) in this role.<ref name="the rise of VPUs">{{cite web |title=A Third Type Of Processor For VR/AR: Movidius' Myriad 2 VPU |website=www.tomshardware.com |url=http://www.tomshardware.com/news/movidiud-myriad2-vpu-vision-processing-vr,30850.html |author=Seth Colaner |date=January 3, 2016 |access-date=May 3, 2016 |archive-date=March 15, 2023 |archive-url=https://web.archive.org/web/20230315180744/https://www.tomshardware.com/news/movidiud-myriad2-vpu-vision-processing-vr,30850.html |url-status=live }}</ref>