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Computer vision, image and colour processing.
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Automation > Resources > Technologies > Images processing
Image processing concepts, Colorimetry, Standards.
The goal of the computer vision is to extract informations from digital images. In this way it is a part of the instrumentation.
The complex technologies used by machine vision are evolving continuously and become more and more affordable, and consequently relatively popular.
The images computing operated by these machines is used to measure and to analyse objects or actions with the objective to control them, providing the results to robots, programmable logic controllers (PLC) or any other type of controllers.
The capabilities of the processors are increasing continuously, and the users express the need to use color processing, especially for sight control and look control of the final products and their packing.
The important amount of solutions available on the market of industrial machine vision has led some providers to standardize the exchanges of data between the vision systems and their environment.
The constraints imposed by some application in term of volume of informations to exchange and in term of response time have inclined manufacturers to propose solutions to adapt networking to vision process.
Machine vision basics, Vision Systems Laboratory, Machine Vision, CVOnline, Computer Vision Group.
This is a complete and very useful course about image processing and machine vision fundamentals.
It can be considered as a reference for these matters.
National Instruments - www.ni.com
Bruce G. Batchelor et Paul F. Whelan
In complement of the National Instrument's document above, a so complete and very useful course about image processing and machine vision, especially related with the industry.
It includes basic machine vision techniques, pattern recognition, intelligent image processing, lighting, multi-camera systems, controlling external devices (robots, tools), colour image recognition, examples of intelligent vision applications, proverbs and more.
This is a list of observations, comments, suggestions, etc based upon our direct and our colleagues' experiences.
It is offered in a light-hearted manner, but encapsulates some important lessons that we have learned but which are unfortunately not universally acknowledged.
We hope it will bring enlightenment and promote discussion among our colleagues.
Vision Systems Laboratory - http://elm.eeng.dcu.ie/~vsg/ - at Dublin City University - www.dcu.ie.
Algorithms, Approximations and Heuristics.
Pr. Bruce G. Batchelor
Robert B. Fisher - School of Informatics - University of Edinburgh (United Kingdom)
CVonline - http://homepages.inf.ed.ac.uk/rbf/CVonline/
The Computer Vision Group - www.cs.cmu.edu/~cil/vision.html
Webexhibits, Colour technology.
Causes of colour
History of Pigments through the ages and the civilizations.
This exhibit is a public service of the Institute for Dynamic Educational Advancement (IDEA). - www.idea.org
Technical aspects of video.
Charles Poynton - www.poynton.com
Genicam, EMVA 1288.
"The goal of GenICam is to provide a generic programming interface for all kinds of cameras.
No matter what interface technology (GigE Vision,
Camera Link, 1394 DCAM)
they are using or what features they are implementing, the application programming interface (API) should be always the same."
"EMVA has launched an initiative to define a unified method to measure, compute and present specification parameters for cameras and image sensors used for machine vision applications.
Application of this standard will be at the benefit of the customers of vision components component manufacturers.
It will avoid misunderstanding and reduce pre and post support cycles.
The chosen parameter definitions are based on physical properties and units.
The standard comprises the mathematical model behind the parameters, the measurement setup and the matching of the measurement data to the model as well as the data presentation."
EMVA - The European Machine Vision Association - www.emva.org
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