Computer Vision in Industry / Applications of Computer Vision (EX)

Course Details


Robert Sablatnig
Matthias Wödlinger




Exkursion (EX)



This excursion with lecture is an elective course in the Module Applications of Computer Vision in the Visual Computing Master.
The elective course ” Computer Vision in Industry” (aka Applications of Computer Vision) is a 2h lecture/ excursion combination held in winter terms by Robert Sablatnig and Matthias Wödlinger. EX means that the course consists of a lecture part and an excursion part. Each component comprises 50% of the overall course content and activities. Robert Sablatnig holds the lecture part at at the beginning of the semester and covers theoretical foundations, core concepts, and relevant background information necessary to understand the subject matter. The guided excursion part is planned and conducted during the latter half of the semester by Matthias Wödlinger and involves practical, hands-on experiences that complement the theoretical knowledge gained during the lectures. It includes guided field trips, on-site observations, and interactive sessions that provide real-world insights and applications of the concepts learned.

The course is structured into two components:

1. Lecture Component: This includes six lectures and an examination.
2. Practical Component: This involves one excursion and four group meetings. The practical work culminates in a final oral presentation and a written report detailing the results achieved by the group.

If you have questions about the excursion or you have trouble finding the link, please send an email to


What are the basic concepts of computer vision, and how are they applied in various industrial contexts? This course aims to answer these questions by explaining the creation of digital images using digital cameras and the subsequent steps to extract information from these images automatically.

The starting point are digital images and their creation, followed by an in-depth look at classical image processing techniques such as image enhancement and compression. The next step involves developing digital filters and segmentation techniques to extract specific information. The course illustrates basic concepts, fundamental problems, simple solutions, and standard fields of image processing applications through application examples. No prior knowledge of image processing is required, but a basic understanding of mathematics is necessary.

The exercise group work involves participating in an excursion and documenting the problems and solutions encountered in this computer vision application. At the end of the semester, the group’s findings will be presented orally and in a written report.

Aims of the Course:

The main goal of the course is to provide a foundational understanding of both the theory and practice of computer vision and its application to various case studies. Key concepts include image acquisition, digital images, digital filters, local and global operators, and segmentation techniques, focusing on their practical applications.

Requirements to pass the course

The slides regarding the winter term 2020/21 excursion excursion can be found here.

Each group must submit one written report (maximum 30 pages) electronically in PDF format, including the following:

  1. List of Participants and Functions (detailing who contributed what)
  2. Abstract (written by the Editor)
  3.  Four pages per student, covering references, introduction, problem statement, solution/discussion of state-of-the-art approaches, and conclusion
  4. Presentation Slides

Additionally, each student will deliver one presentation (maximum 8 minutes per student).

Examples from a previous semester:

Registration for the course

Registration for the course is required and can be completed through the VUT teaching platform, TISS.


The examination is conducted in written form.

Time and Place

The lectures are held on Mondays at 13:15 sharp in Seminarraum FAV 01 A (Seminarraum 183/2)
The course begins with a general preliminary discussion on October 7th, 2024,13:00 c.t.

The full schedule can be seen here: Schedule