Research
The group carries out basic and applied research in industrial image processing. We develop methods, algorithms and system-technical solutions for image acquisition, image processing and evaluation for application, especially in the fields of quality assurance and process control in production, robotics, food industry, construction industry, medical technology and security technology. The main areas of research include: ...
Study - Teaching
Driven by the rapid development of computer technology and the increasing use of artificial intelligence (AI) methods, image processing is more and more penetrating all areas of life, especially to meet industrial requirements for solving tasks of control and quality assurance of manufacturing processes. But image processing methods and systems are also increasingly being used in many other areas of application, such as communication, medicine, traffic, services, etc.
Within teaching lectures, seminars/exercises and practical courses are offered in the fields of basics of image processing, industrial 2D-/3D-image processing, system technology and system theory of image processing, quality assurance/quality management and technical reliability.
In the context of scientific assistances, project seminars, student research projects, diploma, bachelor and master theses, students are integrated into the research projects of the group. In addition, internships or thesis work to be carried out in industrial companies is supervised....
Team
The team of the group headed by Prof. Notni consists of experienced and young scientists.
The employees are supported in their research projects by students in the context of their qualifying work. In the research projects there is close cooperation with research institutes and industrial partners....
Publications
Junger, C.; Fütterer, R.; Rosenberger, M.; Notni, G.
FPGA-based multi-view stereo system with flexible measurement setup
In: Measurement: sensors, ISSN 2665-9174, Bd. 24 (2022), 100425, S. 1-9 ...
Horn, R.; Rosenberger, M.; Golomoz, A.; Fütterer, R.; Dittrich, P.-G.; Nestler, R.; Notni, G.
Investigations on the potential application of machine vision lenses for depth measurement by exploiting chromatic aberrations
In: Measurement: sensors, ISSN 2665-9174, Bd. 23 (2022), 100410, S. 1-9 ...
Walther, D,; Schmidt, L.; Schricker, K.; Junger, C.; Bergmann, J. P.; Notni, G.; Mäder, P.
Automatic detection and prediction of discontinuities in laser beam butt welding utilizing deep learning
In: Journal of advanced joining processes, ISSN 2666-3309, Bd. 6 (2022), 100119, S. 1-11 ...
We would like to thank APIS Informationstechnologien GmbH for their friendly support and the free provision of the FMEA software APIS IQ-Software for teaching and research.
