Welcome to the homepage of the lecture

Image Processing and Computer Vision

Summer Term 2021

Image Processing and Computer Vision

Three Teaching Awards (2 in Computer Science, 1 in Mathematics)

Prof. Joachim Weickert
Virtual office hour: Tuesday, 14:15 - 15:15.

Coordinator of tutorials: Michael Ertel
Virtual office hour: Wednesday, 9:00 - 10:00.

Summer Term 2021

Lectures (4h) with theoretical and programming assignments (2h);
(9 ETCS points)

Online lectures based on the Zoom platform: (privacy information):
Tuesday, 10:15-12:00
Friday, 10:15-12:00

First lecture: Tuesday, April 13
Zoom link:
The Zoom link for forthcoming lectures and the password for downloading the slides will be e-mailed to registered participants on the afternoon of April 15.

Online Tutorials: 2 hours each week; see below.

NewsType of LecturesPrerequisitesTutorialsRegistrationWritten ExamsContentsSelf TestMaterial for the Programming AssignmentsExample Solutions for the AssignmentsLiterature

08.10.2021: The results of the second written exam are now online.

04.10.2021: Opportunity for exam inspection:
Monday, October 11, Lecture Hall 001, Building E1 3. You can find your time slot for the exam inspection here.

04.10.2021: The seating for the second exam is now available.

02.08.2021: Opportunity for exam inspection:
Wednesday, August 4, Lecture Hall 001, Building E1 3. You can find your time slot for the exam inspection here.

02.08.2021: The results of the first written exam are now online.

27.07.2021: The seating for the first exam is now available.

22.07.2021: A list of students admitted to the exams is now available.

15.04.2021: Registered students have been added to the mailing list of their tutorial. If you have not received a welcoming email to your student account, contact Michael Ertel.

15.04.2021: Registered students have been added to the ipcv21 mailing list. If you have not received a welcoming email to your student account, contact Michael Ertel.

15.04.2021: The registration is now closed.

13.04.2021: Registration is now open.

This class gives a broad introduction to the mathematically well-founded and model-based areas of image processing and computer vision. These fields are important in numerous applications including medical image analysis, computer-aided quality control, robotics, computer graphics, multimedia, data science, machine learning, and artificial intelligence. The class is required for starting a bachelor thesis in our group.

It is planned that this class will be continued in the winter term by the class "Differential Equations in Image Processing and Computer Vision" which will bring you closer to our research topics. Both classes are required to pursue a master thesis in our group.

This course is suitable for students of Visual Computing, Mathematics, Computer Science, Mathematics and Computer Science, Data Science and Artificial Intelligence, Bioinformatics, Mechatronics, and Physics. It counts e.g. as a visual computing core area course within the Visual Computing program, and as a core course (Stammvorlesung) within Mathematics or Computer Science.

It is based on undergraduate mathematical knowledge from the first three semesters (such as "Mathematics for Computer Scientists I-III"). For the programming assignments, some elementary knowledge of C is required. The lectures are given in English.

In the online tutorials we discuss the homework assignments (theory and programming). The programming assignments give an intuition about the way how image processing and computer vision algorithms work, while the theoretical assigments provide additional insights, also from a mathematical perspective.

For the homework assignments you can obtain up to 24 points per week. To qualify for both exams you need 50 percent of all possible points. Working in groups of up to three people is permitted and strongly recommended, but all persons must be in the same tutorial group.

By presenting your solution to a homework problem in the tutorials, you can earn 2 bonus points.

If you have questions concerning the tutorials, please do not hesitate to contact Michael Ertel.

Seven online groups are scheduled for Tuesday and Wednesday:

  • Group T1: Tuesday, 12:15-14:00.
    Tutor: Yesie Brama.
    Office hour: Tuesday, 14:00-15:00.

  • Group T2: Tuesday, 14:15-16:00 (tutor understands German).
    Tutor: Kristina Schaefer.
    Office hour: Friday, 14:30-15:30.

  • Group T3: Tuesday, 16:15-18:00.
    Tutor: Erik Johnson.
    Office hour: Thursday, 10:00-11:00.

  • Group W1: Wednesday, 10:15-12:00 (tutor understands German).
    Tutor: Paul Bungert.
    Office hour: Wednesday, 12:00-13:00.

  • Group W2: Wednesday, 12:15-14:00.
    Tutor: Yassir Janah.
    Office hour: Wednesday, 14:30-15:30.

  • Group W3: Wednesday, 14:15-16:00.
    Tutor: Erik Johnson.
    Office hour: Thursday, 14:00-15:00.

  • Group W4: Wednesday, 16:15-18:00.
    Tutor: Aditya Dhall.
    Office hour: Thursday, 15:00-16:00.

If you have difficulties with the programming assignments, feel free to consult our

  • Optional Guided Programming (OGP) Helpdesk: Tuesday, 18:15-20:00
    Please send e-mail for online appointments to Michael Ertel.

first The tutors can be reached via the mail addresses:
ipcv-# -- at -- mia.uni-saarland.de
where # has to be replaced by t1, t2, t3, w1, w2, w3, and w4, respectively.

You could register for this course and the tutorial groups between Tuesday, April 13, 2021, 14:00 and Thursday, April 15, 2021, 12:00. We use Zoom as online teaching platform. Please make sure that you have access to it.

Please do not forget to register also in the HISPOS/LSF system (apart from Erasmus students). This system administrates your exam admission and your grades. It will allow registrations as of April 19, 2021. Information on exam registration can be found here.

It is planned to have two written exams. Changes due to the development of the COVID-19 pandemic cannot be excluded. We will announce any changes of the exam dates as soon as possible.

The first exam takes place on July 29, 14:00-17:00.
The second exam takes place on October 6, 14:00-17:00.

In order to qualify for the exams you need 50 percent of all possible points from the homework assignments. In case of qualification, you are allowed to take part in both exams. The better grade counts. Each exam counts as an individual attempt.

Both exams will be closed book exams. You will have to follow these rules:

  • You are allowed and obliged to bring three things to your desk only: Your student ID card (Studierendenausweis), a ball-pen that has no function other than writing, and a so-called cheat sheet. This cheat sheet is a A4 page with formulas or important equations from the lecture. Please note that the cheat sheet has to be handwritten by yourself. It will be collected at the end of the exam, and you can get it back at the exam inspection.
  • Everything else has to be deposited at the walls of the exam hall. In particular, electronic devices (including your cell phone), bags, jackets, briefcases, lecture notes, homework and classroom work solutions, additional handwritten notes, books, dictionaries, and paper are not allowed at your desk.
  • Please keep your student ID card ready for an attendance check during the exam.
  • Do not use pencils or pens that are erasable with a normal rubber.
  • You are not allowed to take anything with you that contains information about the exam.
    A violation of this rule means failing the IPCV course.
  • You must stay until the exam is completely over.
  • You have to wear a medical face mask (satisfying the medical mouth and nose protection, FFP2, or KN95 standards).

If a student is unable to attend the written exams due to reasons beyond his/her control (e.g. because of an illness (medical certificate required immediately), travel restrictions, or another exam at the same day), it is planned to provide alternative options such as an online oral exam.

A list of students that are admitted to the written exams is now available here. If you do not find your matriculation number in the list and you think you should be admitted to the exams, please contact Michael Ertel.

Here is the distribution of places by family name (i.e. surname, last name) for the first exam that takes place on Thursday, July 29, 2021 from 14:00 to 17:00:

Students A - J: Building E2.5, Lecture Hall 001
Students K - Z: Building E2.2, Günter Hotz Lecture Theatre

The results of the first written exam can be found here, and the corresponding distribution of points and grades here.

Each student who has participated in the first written exam has the opportunity to inspect his/her graded solutions in Lecture hall 001 in Building E1.3 on Wednesday, August 4, 2021 from 2:00 p.m. to 5:00 p.m. Due to Covid-19 you are assigned a time slot for the exam inspection. You can see when you should arrive here.

The second exam that takes place on Wednesday, October 6, 2021 from 14:00 to 17:00 will be held at :

Building E2.2, Günter Hotz Lecture Theatre

The results of the second written exam can be found here, and the corresponding distribution of points and grades here.

Each student who has participated in the second written exam has the opportunity to inspect his/her graded solutions in Lecture hall 001 in Building E1.3 on Monday, October 11, 2021. Due to Covid-19 you are assigned a time slot for the exam inspection. You can see when you should arrive here.

Course material is available on this webpage in order to support the teaching and the tutorials, not to replace them. Additional organisational information, examples and explanations that may be relevant for your understanding and the exam are provided in the lectures and tutorials. It is solely your responsibility - not ours - to make sure that you receive this infomation. Here is a preliminary list of the planned contents:


Date Topic
13.04. Foundations I: Definitions, Image Types, Discretisation
16.04. Foundations II: Degradations in Digital Images
(contains classroom assignment P1 and homework H1)
20.04. Foundations III: Colour Perception and Colour Spaces
23.04. Image Transformations I: Continuous Fourier Transform
(contains classroom assignment P2 and homework H2)
27.04. Image Transformations II: Sampling Theorem and Discrete Fourier Transform
30.04. Image Transformations III: Discrete Cosine Transform and Image Pyramids
(contains classroom assignment P3 and homework H3)
04.05. Image Transformations IV: Discrete Wavelet Transform
07.05. Image Compression
(contains classroom assignment P4 and homework H4)
11.05. Image Interpolation


Date Topic
14.05. Point Operations
(contains classroom assignment P5 and homework H5)
18.05. Linear Filters I: System Theory
22.05. Linear Filters II: Derivative Filters
(contains classroom assignment P6 and homework H6)
25.05. Linear Filters III: Detection of Edges and Corners
28.05. Nonlinear Filters I: Morphology and Median Filters
(contains classroom assignment P7 and homework H7)
01.06. Nonlinear Filters II: Wavelet Shrinkage, Bilateral Filters, NL-Means
04.06. Nonlinear Filters III: Nonlinear Diffusion Filtering
(contains classroom assignment P8 and homework H8)
08.06. Global Filters I: Discrete Variational Methods
11.06. Global Filters II: Continuous Variational Methods
(contains classroom assignment P9 and homework H9)
15.06. Global Filters III: Deconvolution Methods
18.06. Texture Analysis
(contains classroom assignment P10 and homework H10)


Date Topic
22.06. Segmentation I: Thresholding, Region Growing, Region Merging
25.06. Segmentation II: Watersheds and Optimisation Methods
(contains classroom assignment P11 and homework H11)
29.06. Image Sequence Analysis I: Local Methods
02.07. Image Sequence Analysis II: Variational Methods
(contains classroom assignment P12 and homework H12)
06.07. 3-D Reconstruction I: Camera Geometry
09.07. 3-D Reconstruction II: Stereo
(contains classroom assignment P13 and homework H13)
13.07. 3-D Reconstruction III: Shape-from-Shading
16.07. Object Recognition I: Hough Transform and Invariants
20.07. Object Recognition II: Eigenspace Methods
23.07. Summary, Conclusions, Outlook

There is no specific text book for this class, but many of our image processing topics are covered in one of the following books:

  • J. Bigun: Vision with Direction. Springer, Berlin, 2010.
  • R. C. Gonzalez, R. E. Woods: Digital Image Processing. Addison-Wesley, International Edition, 2017.
  • K. D. Tönnies: Grundlagen der Bildverarbeitung. Pearson Studium, München, 2005.

Computer vision books include

  • R. Klette: Concise Computer Vision. Springer, London, 2014.
  • R. Szeliski: Computer Vision: Algorithms and Applications. Springer, New York, 2010.
  • E. Trucco, A. Verri: Introductory Techniques for 3-D Computer Vision. Prentice Hill, Upper Saddle River, 1998.

These and further books can be found in the mathematics and computer science library.
Furthermore, there is an interesting online compendium, where many researchers have written survey articles.
If you are looking for a specific reference, check out the Annotated Computer Vision Bibliography.
Many highly cited articles can be found via the Google Scholar webpage.

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