Imaging Sensor Systems
- Faculty
Faculty of Engineering and Computer Science
- Version
Version 1 of 23.01.2026.
- Module identifier
11M0485
- Module level
Master
- Language of instruction
German
- ECTS credit points and grading
5.0
- Module frequency
only winter term
- Duration
1 semester
- Brief description
The use of cameras and other imaging technologies as sensor systems offers innovative solutions in automation technology and many other areas, and imaging has established itself as an interdisciplinary field. A problem- and system-oriented approach is used to develop solutions for complex tasks, from lighting and the object itself to the interpretation of the evaluated data. After completing the module, students will be familiar with the technological areas of imaging systems, from image capture to image processing, and will have acquired the skills to design and implement projects in the field of imaging, supplemented by practical experience.
- Teaching and learning outcomes
- Fundamentals of imaging sensor technology
- Pixel structures and system architectures
- Characterisation of imaging systems
- Imaging camera systems (examples: spectral imaging, high-speed cameras, light-shadow sensors, 3D imaging)
- Image capture (formats, colour spaces)
- Image processing (point operations, filters, object extraction)
- Applications
- Overall workload
The total workload for the module is 150 hours (see also "ECTS credit points and grading").
- Teaching and learning methods
Lecturer based learning Workload hours Type of teaching Media implementation Concretization 30 Lecture - 15 Laboratory activity - Lecturer independent learning Workload hours Type of teaching Media implementation Concretization 60 Creation of examinations - 15 Preparation/follow-up for course work - 15 Study of literature - 15 Presentation preparation -
- Graded examination
- Project Report, written or
- oral exam or
- Written examination
- Ungraded exam
- Field work / Experimental work
- Remark on the assessment methods
The experimental work can be carried out in the form of an ‘advanced practical course’: in addition to the tasks set out in the experiment instructions, students carry out a task they have set themselves using the technologies involved in an experiment.
- Exam duration and scope
Graded examination performance:
- Project report (written): approx. 15–20 pages; explanation: approx. 20 minutes
- Oral examination: see general section of the examination regulations
- Written examination: see study regulations
Ungraded examination performance:
- Experimental work: Experiment: approx. 5 experiments in total
- Recommended prior knowledge
The module requires basic knowledge of physics and electronics, digital signal processing, programming skills and mathematics (especially vector and matrix calculus).
- Knowledge Broadening
Students are familiar with the concepts and many system-related approaches to imaging sensor technology. They also know basic image processing algorithms for extracting knowledge from images.
- Knowledge deepening
Students are able to develop technological solutions for practical problems using imaging sensor technologies and to specify the technological steps required for their implementation.
- Application and Transfer
Students gain practical experience in the problem-oriented design and application of imaging sensor systems. They also learn how to apply and combine image processing algorithms appropriately.
- Academic Innovation
Students can independently design and implement problem-oriented system solutions based on imaging sensor technologies and image processing algorithms. Imaging sensor technologies/imaging should be understood as a system technology that has strong links to electronics, computer science, sensor technology and human vision; systems thinking is therefore firmly anchored in the subject.
- Literature
J. Beyerer, F. Puente Leon, C. Frese: Automatische Sichtprüfung, SpringerVieweg, 2. Aufl., 2016
W. Burger, M. J. Burge: Digitale Bildverarbeitung. Springer, 2. Aufl., 2006
A. Erhardt: Einführung in die Digitale Bildverarbeitung. Vieweg+Teubner, 2008
R. C. Gonzalez, R. E. Woods: Digital Image Processing, Pearson, 3rd ed. , 2008
B. J?hne: Digitale Bildverarbeitung. Springer, 2001
P. Soille: Morphologische Bildverarbeitung. Springer, 1998
K. D. T?nnjes: Grundlagen der Bildverarbeitung. Pearson Studium, 2005
- Applicability in study programs
- Mechatronic Systems Engineering
- Mechatronic Systems Engineering M.Sc. (01.09.2025)
- Electrical Engineering (Master)
- Electrical Engineering M.Sc. (01.09.2025)
- Mechanical Engineering (Master)
- Mechanical Engineering M.Sc. (01.09.2025)
- Person responsible for the module
- Weinhardt, Markus
- Teachers
- Lang, Bernhard
- Weinhardt, Markus