FRAMOS is jointly hosting a two-day online training on the EMVA 1288 standard. The online course will take place on May 27th &28th. Participants will gain experience with EMVA 1288 standard measurements, using the required measuring equipment. They will learn the optimum setup, and how to analyse the results. The course is targeted to all who applies the EMVA 1288 standard, either in development or when testing and comparing cameras. The speaker is Prof. Dr. Bernd Jähne, a member of the EMVA board with many years of experience in teaching and education..
The online training will be conducted in English and registration is now open for anyone who wishes to participate. At the end of the course, participants will have the option of taking a written examination to gain certification as an EMVA 1288 Expert. The certificate shows that the holder can successfully carry out measurements in accordance with EMVA 1288, and correctly interpret the results.
EMVA 1288 – a worldwide standard
For almost ten years, the EMVA 1288 standard has been used worldwide for an objective and application-oriented characterisation of industrial cameras. It covers both area-scan and line-scan cameras with monochrome and colour sensors. Hosted by FRAMOS, the training event offers participants the opportunity to gain User or Expert certification (optional). The User level includes the necessary knowledge to select the best possible camera(s) for a given application based on data sheets. The Expert level is designed for all those who want to develop cameras or perform EMVA 1288 measurements themselves.
About the speaker
Prof. Dr. Bernd Jähne founded the Heidelberg Collaboratory for Image Processing (HCI) at Heidelberg University.
He has been EMVA 1288 Chair since 2008, and a member of the EMVA board since 2015. He is the author of several books, including a standard textbook on image processing that has been published in several languages.
When: May 27 & 28, 2020
Where: Online Training
Price: 499,00 €
For more details and to register, please go here: