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 hoursType of teachingMedia implementationConcretization
30Lecture-
15Laboratory activity-
Lecturer independent learning
Workload hoursType of teachingMedia implementationConcretization
60Creation of examinations-
15Preparation/follow-up for course work-
15Study of literature-
15Presentation 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