Imaging Quality Assurance
- Faculty
Faculty of Engineering and Computer Science
- Version
Version 1 of 16.03.2026.
- Module identifier
11M0674
- Module level
Master
- Language of instruction
English
- ECTS credit points and grading
5.0
- Module frequency
only summer term
- Duration
1 semester
- Special features of the module
Language English
- Brief description
Imaging is a key technology in quality assurance. The knowledge about a large number of options for image capturing, image processing and data reduction to parameters is one major goal of the module. The interpretation of parameters with respect to quality is of highest importance in practice, thus this topic will be covered by lab experiments including self-selected tasks. Several examples from different field of applications of imaging quality assurance will be included in the lecture, the lab experiments and the projects.
- Teaching and learning outcomes
1-Introduction to applied image processing
2-Sensors and camera systems for machine vision
3-Other image-based sensor systems in quality assurance
4-Image processing and quality parameters
5-Applications from industrial imaging, medical technology, food industry and agriculture
6-Application of image-based systems (such as color cameras, distance cameas, spectral imaging, light curtain imaging, high-speed cameras)
7-Software tools, algorithms and statistical methods for image and quality parameter interpretation
- 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 25 Lecture Presence or online - 10 Learning in groups / Coaching of groups Presence - 10 Laboratory activity Presence - Lecturer independent learning Workload hours Type of teaching Media implementation Concretization 25 Preparation/follow-up for course work - 50 seminar paper - 30 Work in small groups -
- Graded examination
- Project Report, written
- Ungraded exam
- Field work / Experimental work
- Remark on the assessment methods
A presentation of the project report will be given in the group. The experimental lab will be performed as an "advanced lab" (standard task, specific task, task defined by the students).
- Exam duration and scope
EA: ca. 5 laboratory experiments à 90 min
PSC: 10-20 pages
- Recommended prior knowledge
Basic knowledge in programming, mathematics, electronics and physics.
- Knowledge Broadening
The students have knowledge about different imaging technologies and image analysis.
- Knowledge deepening
The students have knowledge about specific potentials of Image Quality Assurance.
- Knowledge Understanding
The students know about the risks for imaging applications in quality assurance.
- Application and Transfer
The students have practical experiences with different imaging systems, both for data acquisition as well as for image analysis and interpretation. The students are able to evaluate the implementation of imaging quality assurance for a given application.
- Communication and Cooperation
The students are able to present and discuss imaging quality assurance applications, this includes the following aspects: problem description, imaging setup, measurements, statistical analysis and interpretation.
- Literature
Computer & Machine Vision, E.R. Davies, Academic Press, 2012
Digital Image Processing using MATLAB, R. Gonzales, R. Woods, S. Eddines, Gatesmark Publishing, 2009
Optical Monitoring for Fresh and Processed Agricultural Crops, M.Zude, CRC Press, 2008
For German students:
Einführung in die Digitale Bildverarbeitung, A. Erhardt, Vieweg+Teubner, 2008
Qualitätsmanagement für Ingenieure, G.Linß, Carl Hanser Verlag (relevant sections are also supported in English), 2022
- Applicability in study programs
- Computer Science
- Computer Science M.Sc. (01.09.2025)
- Mechatronic Systems Engineering
- Mechatronic Systems Engineering M.Sc. (01.09.2025)
- Person responsible for the module
- Thiesing, Frank
- Teachers
- Pamornnak, Burawich