183.590 Applications of Computer Vision
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2022W, EX, 2.0h, 3.0EC
TUWELQuinn ECTS survey


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: EX Excursion
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to identify, explain and contrast the most important theories, principles, concepts and algorithms of Computer Vision applications. Their knowledge and understanding corresponds to the status of specialist literature in the field of computer vision for applications. They are able to apply appropriate formal-mathematical methods for modeling, abstraction, solution finding and evaluation, and gain problem-formulation and problem-solving skills. Students can collect, compile, evaluate and interpret information relevant to Computer Vision, determine requirements and constraints in various areas of computer vision, and apply their knowledge acquired to complex computer vision tasks, develop solutions to problems and arguments , Students will be able to identify areas of computer vision themselves, tap into them, formulate solutions to problems and exchange views with others. The students learn to assess their own abilities and limits and acquire the ability to criticize their own and others' work. The students learn self-organization and self-responsibility to independently solve tasks.

Subject of course

What are the basic concepts of Image Processing and how are they used in different Applications? The course tries to answer these questions by describing the creation of digital images using digital cameras and the subsequent steps in order to derive information kept in digital images automatically. The starting point are digital images and their creation. Then a closer look is taken into classical image processing techniques like image enhancement and compression. The next step consists in the development of digital filters and segmentation techniques in order to be able to extract specific information. Using examples in applications the courses tries to show the basic concepts, basic problems and simple solutions and typical fields of applications of image processing. Previous knowledge in the area of image processing is not required, however a basic mathematical understanding is necessary. The work in the exercise group consists of attending an excursion and the description of the problems and the solutions in this image processing application, or alternatively in solving a specific problem of image processing in a lab exercise. At the end of the semester the results of the work in the group should be presented orally and in a written report.

Teaching methods

Frontal presentation and written exam in the independent solving of subject-related examples and submissions in the foreground. The course consists of a lecture part and an excursion part, in which real applications of computer vision in the industrial environment are explained in more detail and examined in groups. The contents and concepts described will be explained in the course of the lecture unit and presented clearly in practice in the excursion section. The findings gained during the excursion are discussed in the group and presented in written and oral form by the group.

Mode of examination




Course dates

Mon13:00 - 15:0003.10.2022Seminarraum FAV 01 A (Seminarraum 183/2) ACV Introduction
Mon13:00 - 15:0010.10.2022 - 23.01.2023Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Applications of Computer Vision - Single appointments
Mon03.10.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) ACV Introduction
Mon10.10.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon17.10.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon24.10.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon31.10.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon07.11.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon14.11.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon21.11.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon28.11.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon05.12.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon12.12.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon19.12.202213:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon09.01.202313:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon16.01.202313:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture
Mon23.01.202313:00 - 15:00Seminarraum FAV 01 A (Seminarraum 183/2) Lecture

Examination modalities

Excursion participation, preparation of excursion report and presentation, written exam


DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Mon13:00 - 15:0029.01.2024Seminarraum FAV 01 A (Seminarraum 183/2) written17.01.2024 00:00 - 28.01.2024 23:55TISSExamination

Course registration

Begin End Deregistration end
30.08.2022 00:00 31.10.2022 00:00 31.10.2022 00:00


Study CodeObligationSemesterPrecon.Info
066 932 Visual Computing Mandatory elective


No lecture notes are available.