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European Machine Vision Association Names New President

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The European Machine Vision Association (EMVA) has announced that Chris Yates has been elected as president of the EMVA, effective Jan. 1, 2020. The decision to elect the new president was agreed on by the EMVA board of directors during a recent board meeting in Berlin where Chris Yates was elected unanimously.
EMVA President-elect Chris Yates. Courtesy of EMVA.
EMVA President-elect Chris Yates. Courtesy of EMVA.

Yates will succeed Jochem Herrmann, the current president of the EMVA who has held the role since 2015 and decided to step down to spend more time with his family. He is co-founder and chief scientist of Adimec BV. Herrmann will continue to be a member of the board of directors into 2020.

Yates is the director of advanced technology within the safety, sensing, and connectivity business of Rockwell Automation. He served as CEO and founder of Odos Imaging prior to the company’s 2017 acquisition by Rockwell Automation. He holds a Ph.D. from Imperial College London and has held a number of senior roles in early-stage companies, concentrating on the effective translation of novel technology to products in the market.

EMVA is a non-profit member-owned organization which represents more than 120 companies, institutes and organizations. The EMVA hosts several important standards used throughout the machine vision industry including the GenICam series used to provide a consistent, device independent interface to machine vision hardware, the EMVA1288 standard used for bench-marking performance of industrial cameras, and the newly initiated Open Optics Camera Interface (OOCI) standard which addresses the connectivity of camera lenses within a machine vision system, and the new emVISION initiative addressing standardization within embedded vision systems.

Published: December 2019
Glossary
machine vision
Machine vision, also known as computer vision or computer sight, refers to the technology that enables machines, typically computers, to interpret and understand visual information from the world, much like the human visual system. It involves the development and application of algorithms and systems that allow machines to acquire, process, analyze, and make decisions based on visual data. Key aspects of machine vision include: Image acquisition: Machine vision systems use various...
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