Meyer Named EMVA Young Professional 2019

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COPENHAGEN, Denmark, May 21, 2019 — The European Machine Vision Association (EMVA) has recognized Johannes Meyer with its Young Professional Award 2019 for his work on “Light Field Methods for the Visual Inspection of Transparent Objects.” The presentation was made May 18 to the Karlsruhe Institute of Technology graduate at the EMVA business conference in Copenhagen, Denmark.

Meyer developed a sensor system, the laser deflection scanner, which enables the acquisition of high-resolution light fields from transparent samples. Using algorithms, material defects from these light fields can be extracted in real time. In addition, he developed a method for inverse light-field illumination, which suppresses all target structures of the device under test and visualizes defects with high contrast.

Objects made of transparent materials are everywhere; they are used in windshields, in eyeglasses, and as plastic lenses for beam shaping. A visual quality check for material defects such as trapped air bubbles or surface scratches is essential. This work is very tedious for human workers, and the results are often subjective, with defects often overlooked. Automated inspection of complex, transparent objects remains a challenge for machine vision.

Transparent objects and material defects contained in them influence the propagation direction of light passing through them. For defect detection, therefore, the complete field of light must be considered — not only the location, but also the propagation direction of the light rays. In this work, the light-field concept was therefore integrated into the three main components of a test system: the lighting, image acquisition, and image processing component.

The annual EMVA award honors the extraordinary and innovative work of students or newcomers to the field of image processing. With the award, EMVA specifically encourages students to focus on the technical challenges of machine vision and apply the latest imaging research findings to the practical needs of the industry.

Published: May 2019
machine vision
Interpretation of an image of an object or scene through the use of optical noncontact sensing mechanisms for the purpose of obtaining information and/or controlling machines or processes.
BusinessEuropemachine visionLasersImagingJohannes MeyerEuropean Machine Vision Associationawards

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