Editing Machine vision (section)

===Imaging===

The imaging device (e.g. camera) can either be separate from the main image processing unit or combined with it in which case the combination is generally called a [[smart camera]] or smart sensor.<ref>{{cite book | title = Smart Cameras | editor = Belbachir, Ahmed Nabil| publisher = Springer | date = 2009 | isbn = 978-1-4419-0952-7}}{{page needed|date=December 2012}}</ref><ref name= "VSD201302">{{cite journal| url=http://www.vision-systems.com/articles/print/volume-18/issue-2/departments/leading-edge-views/explore-the-fundamentals-of-machine-vision-part-i.html  | title=Explore the Fundamentals of Machine Vision: Part 1| volume=18 | issue=2 | date=February 2013 |author=Dechow, David |journal=Vision Systems Design |pages=14–15| access-date=2013-03-05}}</ref> Inclusion of the full processing function into the same enclosure as the camera is often referred to as embedded processing.<ref name ="PhotonicsSpectra2019">''Critical Considerations for Embedded Vision Design''  by Dave Rice and Amber Thousand ''Photonics Spectra'' magazine published by Laurin Publishing Co. July 2019 issue Pages 60-64</ref> When separated, the connection may be made to specialized intermediate hardware, a custom processing appliance, or a [[frame grabber]] within a computer using either an analog or standardized digital interface ([[Camera Link]], [[CoaXPress]]).<ref name = coaxexpress>{{cite journal| url=http://www.vision-systems.com/articles/2011/05/coaxpress-standard-camera-frame-grabber-support.html  | title=CoaXPress standard gets camera, frame grabber support | date= May 31, 2011 |author=Wilson, Andrew  |journal=Vision Systems Design |access-date=2012-11-28}}</ref><ref name = VSDCompliantCameras>{{cite journal| url=http://www.vision-systems.com/articles/2012/11/cameras-certified-as-compliant-with-coaxpress-standard.html | title=Cameras certified as compliant with CoaXPress standard | author=Wilson, Dave |journal=Vision Systems Design | date= November 12, 2012 |access-date=2013-03-05}}</ref><ref name = Davies2nd/><ref name = Dinev>{{cite journal |author=Dinev, Petko |title=Digital or Analog? Selecting the Right Camera for an Application Depends on What the Machine Vision System is Trying to Achieve |journal=Vision & Sensors |date=March 2008 |pages=10–14 |url=http://www.visionsensorsmag.com/Articles/Feature_Article/BNP_GUID_9-5-2006_A_10000000000000276728 |archive-url=https://web.archive.org/web/20200314042249/http://www.visionsensorsmag.com/Articles/Feature_Article/BNP_GUID_9-5-2006_A_10000000000000276728 |url-status=dead |archive-date=2020-03-14 |access-date=2012-05-12 }}</ref> MV implementations also use digital cameras capable of direct connections (without a framegrabber) to a computer via [[IEEE 1394|FireWire]], [[USB]] or [[Gigabit Ethernet]] interfaces.<ref name = Dinev/><ref name = VSDInterfaces>{{cite journal | url=http://www.vision-systems.com/articles/print/volume-16/issue-12/features/looking-to-the-future-of-vision.html | title=Product Focus - Looking to the Future of Vision | author=Wilson, Andrew | journal=Vision Systems Design |volume=16| issue=12 | date=December 2011 |access-date=2013-03-05}}</ref>

While conventional (2D visible light) imaging is most commonly used in MV, alternatives include [[Multispectral image|multispectral imaging]], [[hyperspectral imaging]], imaging various infrared bands,<ref name =InfraredVSDApril2011>{{cite journal  |author=Wilson, Andrew | title=The Infrared Choice | journal= Vision Systems Design |date= April 2011 |pages=20–23 | url=http://www.vision-systems.com/articles/print/volume-16/issue-4/features/the-infrared-choice.html |volume=16 |issue=4|access-date=2013-03-05}}</ref> line scan imaging, [[3D imaging]] of surfaces and X-ray imaging.<ref name = NASAarticle>{{cite journal|journal= [[NASA Tech Briefs]] |volume= 35 |issue= 6 |date= June 2011 |title=Machine Vision Fundamentals, How to Make Robots See|author=Turek, Fred D. |pages=60–62 |url= http://www.techbriefs.com/privacy-footer-69/10531 | access-date=2011-11-29}}</ref> Key differentiations within MV 2D visible light imaging are monochromatic vs. color, [[frame rate]], resolution, and whether or not the imaging process is simultaneous over the entire image, making it suitable for moving processes.<ref name = WestHSRT>West, Perry ''High Speed, Real-Time Machine Vision '' CyberOptics, pages 1-38</ref>

Though the vast majority of machine vision applications are solved using two-dimensional imaging, machine vision applications utilizing 3D imaging are a growing niche within the industry.<ref name=DN201202>{{cite journal |title=3D Machine Vison Comes into Focus |author=Murray, Charles J |journal=[[Design News]] |date=February 2012 |url=http://www.designnews.com/document.asp?doc_id=237971 |access-date=2012-05-12 |url-status=dead |archive-url=https://web.archive.org/web/20120605095256/http://www.designnews.com/document.asp?doc_id=237971 |archive-date=2012-06-05 }}</ref><ref name=Davies4th410-411>{{cite book|pages=410–411|author=Davies, E.R. | edition=4th | date=2012 | title=Computer and Machine Vision: Theory, Algorithms, Practicalities | publisher=Academic Press| isbn=9780123869081 | url=https://books.google.com/books?id=AhVjXf2yKtkC&pg=PA410 | access-date=2012-05-13}}</ref> The most commonly used method for 3D imaging is scanning based triangulation which utilizes motion of the product or image during the imaging process. A laser is projected onto the surfaces of an object. In machine vision this is accomplished with a scanning motion, either by moving the workpiece, or by moving the camera & laser imaging system. The line is viewed by a camera from a different angle; the deviation of the line represents shape variations. Lines from multiple scans are assembled into a [[depth map]] or point cloud.<ref name = QualityMagazine/> Stereoscopic vision is used in special cases involving unique features present in both views of a pair of cameras.<ref name = QualityMagazine>''3-D Imaging: A practical Overview for Machine Vision'' By Fred Turek & Kim Jackson   Quality Magazine, March 2014 issue, Volume 53/Number 3  Pages 6-8</ref> Other 3D methods used for machine vision are [[Time-of-flight camera|time of flight]] and grid based.<ref name =QualityMagazine/><ref name =DN201202/> One method is grid array based systems using pseudorandom structured light system as employed by the Microsoft Kinect system circa 2012.<ref name = hybrid>http://research.microsoft.com/en-us/people/fengwu/depth-icip-12.pdf  HYBRID STRUCTURED LIGHT FOR SCALABLE DEPTH SENSING Yueyi Zhang, Zhiwei Xiong, Feng Wu University of Science and Technology of China, Hefei, China Microsoft Research Asia, Beijing, China</ref><ref name = pseudorandom>R.Morano, C.Ozturk, R.Conn, S.Dubin, S.Zietz, J.Nissano, "Structured light using pseudorandom codes", IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (3)(1998)322–327</ref>