Welcome to the homepage of the lecture

Image Processing and Computer Vision

Summer Term 2018

Image Processing and Computer Vision

Prof. Joachim Weickert
Office hour: Tuesday, 14:15 - 15:15.

Coordinator of tutorials: Aaron Wewior
Office hour: Wednesday, 14:15 - 15:15.

Summer Term 2018

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

Tuesday, 10-12 c.t., Building E1.3, Lecture Hall 001
Friday, 10-12 c.t., Building E1.3, Lecture Hall 001

First lecture: Tuesday, April 10, 2018

Tutorials: 2 hours each week; see below.

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

12.10.18: Opportunity for exam inspection:
Tuesday, October 16, Room 4.10, Building E1 7, 2:15 p.m. - 3:15 p.m.

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

26.07.18: Opportunity for exam inspection:
Friday, July 27, Room 4.10, Building E1 7, 1:30 p.m. - 3:30 p.m.

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

20.07.18: The seating for the first written exam is online!

16.07.18: The list of admitted students is online!

26.04.18: The lecture from Tuesday, May 1, will be moved to Monday, April 30, 6-8 p.m., Building E1.3, Lecture Hall 001.
The tutorial for the groups T1,T2 and T2 from Tuesday, October 31, will be moved to Monday, April 30, 4-6 p.m., Building E1.3, Lecture Hall 001.

13.04.18: Registration is closed.

10.04.18: Registration is opened!

23.03.18: Website is online

Broad introduction to mathematically well-founded 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 and artificial intelligence. The classes qualify for starting a bachelor's thesis in our group.

This course is suitable for students of visual computing, mathematics, computer science, bioinformatics, computer and communications technology, and physics. It counts e.g. as a visual computing core course within the visual computing programme, an applied mathematics course within mathematics, or a core course (Stammvorlesung) in computer science.

It is based on mathematical knowledge from the first two semesters. For the programming assignments, some elementary knowledge of C is required. The lectures are given in English.

The tutorials include homework assignments (theory and programming) as well as classroom assignments. The programming assignments give an intuition about the way how image processing and computer vision algorithms work, while the theoretical assigments provide additional mathematical insights. Classroom assignments are supposed to be easier and should guide you gently to the main themes.

For the homework assignments you can obtain up to 24 points per week. Actively participating in the classroom assignments gives you 12 more points per week, regardless of the correctness of your solutions. To qualify for both exams you need 2/3 of all possible points. For 13 weeks, this comes down to 13 x 24 = 312 points. Working in groups of up to 3 people is permitted, but all persons must be in the same tutorial group.

If you miss a tutorial because you are sick, you can still get the points for participation, if you bring a doctor's certificate.

If you have questions concerning the tutorials, please do not hesitate to contact Aaron Wewior.

Six groups are scheduled for Tuesday and Wednesday afternoon:

  • Group T1:
    Tue, 12-14, Building E1.3, Seminar Room 014
    (in English)
    Tutor: Alexander Rath

  • Group T2:
    Tue, 14-16, Building E1.3, Seminar Room 014
    (English only)
    Tutor: Zeeshan Khan Suri

  • Group T3:
    Tue, 16-18, Building E1.3, Seminar Room 014
    (in German)
    Tutor: David Liebemann

  • Group W1:
    Wed, 8-10, Building E1.1, Seminar Room 206
    (in English)
    Tutor: Alexander Köhn

  • Group W2:
    Wed, 14-16, Building E2.5, Seminar Room 1 (U 37)
    (English only)
    Tutor: Hyoseung Kang

  • Group W3:
    Wed, 16-18, Building E1.3, Seminar Room 107
    (English only)
    Tutor: Hyoseung Kang

If you have difficulties with the programming assignments, feel free to participate in

  • Optional Guided Programming (OGP):
    Tue, 18-20, CIP 104 in Building E1.3
    Tutor: Aaron Wewior

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, and w3, respectively.

Due to a public holiday, the tutorials on May 1 have been moved to April 30, 4 p.m. in Lecture Hall 001 in Building E 1.3. All three tutorials will be held in that time slot and it is not mandatory to attend.

Between Tue, April 10, 2018, 14:00 and Fri, April 13, 2018, 13:00, you could register for this course. Registration is now closed. You can still check which group you are finally in.

Please register also in the HISPOS system. Please note that the HISPOS registration is completely independent of the lecture registration and is not administered by us.

There will be two written exams, one at the beginning and one at the end of the semester break.

The first written exam takes place on
Wednesday, July 25, 2018 from 14:00 to 17:00,

The second written exam takes place on
Wednesday, October 10, 2018 from 14:00 to 17:00,

In order to qualify for the exams you need a total amount of 2/3 of all possible points from the homework and classroom assignments. In case of qualification, you are allowed to take part in both exams. The better grade counts, but each exam will count as an attempt individually.

Please check here whether you are admitted to the written exam. If you think that there is an error, please contact Aaron Wewior immediately.

Here is the distribution of places by family name (i.e. surname, last name) for the first exam that takes place on Wednesday, July 25, 2018 from 14:00 to 17:00:

Students A - O: Building E2.2, Günter Hotz Lecture Theatre
Students R - Z: Building E1.3, Lecture Hall 002

For the second exam that takes place on Wednesday, October 10, 2018 from 14:00 to 17:00, all students will be in Building E2.2, Günter Hotz Lecture Theatre.

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.

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 room 4.10 in Building E1.7 on Friday, July 27, 2018 from 1:30 p.m. to 3:30 p.m.

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 room 4.10 in Building E1.7 on Tuesday, October 16, 2018, from 2:15 to 3:15 p.m.

Course material is available on this webpage in order to support the classroom 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.


Date Topic
10.04. Foundations I: Definitions, Image Types, Discretisation
13.04. Foundations II: Degradations in Digital Images
(contains classroom assignment C1 and homework H1)
17.04. Foundations III: Colour Perception and Colour Spaces
20.04. Image Transformations I: Continuous Fourier Transform
(contains classroom assignment C2 and homework H2)
24.04. Image Transformations II: Sampling Theorem and Discrete Fourier Transform
27.04. Image Transformations III: Discrete Cosine Transform and Image Pyramids
(contains classroom assignment C3 and homework H3)
30.04. Image Transformations IV: Discrete Wavelet Transform
This lecture has been moved!
Time and place: 6 p.m.,Building E 1.3, Lecture Hall 001

04.05. Image Compression
(contains classroom assignment C4 and homework H4)
08.05. Image Interpolation


Date Topic
11.05. Point Operations
(contains classroom assignment C5 and homework H5)
15.05. Linear Filters I: System Theory
18.05. Linear Filters II: Derivative Filters
(contains classroom assignment C6 and homework H6)
22.05. Linear Filters III: Detection of Edges and Corners
25.05. Nonlinear Filters I: Morphology and Median Filters
(contains classroom assignment C7 and homework H7)
29.05. Nonlinear Filters II: Wavelet Shrinkage, Bilateral Filters, NL-Means
01.06. Nonlinear Filters III: Nonlinear Diffusion Filtering
(contains classroom assignment C8 and homework H8)
05.06. Global Filters I: Discrete Variational Methods
08.06. Global Filters II: Continuous Variational Methods
(contains classroom assignment C9 and homework H9)
12.06. Global Filters III: Deconvolution Methods
15.06. Texture Analysis
(contains classroom assignment C10 and homework H10)


Date Topic
19.06. Segmentation I: Thresholding, Region Growing, Region Merging
22.06. Segmentation II: Watersheds and Optimisation Methods
(contains classroom assignment C11 and homework H11)
26.06. Image Sequence Analysis I: Local Methods
29.06. Image Sequence Analysis II: Variational Methods
(contains classroom assignment C12 and homework H12)
03.07. 3-D Reconstruction I: Camera Geometry
06.07. 3-D Reconstruction II: Stereo
(contains classroom assignment C13 and homework H13)
10.07. 3-D Reconstruction III: Shape-from-Shading
13.07. Object Recognition I: Hough Transform and Invariants
17.07. Object Recognition II: Eigenspace Methods
20.07. Summary, Conclusions, Outlook

The following self-test problem sheet contains 6 problems, which are intended to be similar in style and difficulty to a 180-minutes written exam.

13.07. Self Test Problem Sheet
13.07. Self Test Solution

Here you can download material for the programming assignments.

13.04. Assignment H1: Noise, Quantisation, and Dithering
20.04. Assignment H2: Colour Spaces and Subsampling
27.04. Assignment H3: Fourier Filtering
04.05. Assignment H4: Discrete Cosine Transform
11.05. Assignment H5: Point Transformations
18.05. Assignment H6: Linear Filters
25.05. Assignment H7: Edge and Corner Detection, Morphology
01.06. Assignment H8: Wavelet Shrinkage, NL-Means
08.06. Assignment H9: Whittaker-Tikhonov Regularisation, Unsharp Masking
15.06. Assignment H10: Texture Inpainting, Deconvolution
22.06. Assignment H11: Toboggan Watershed Segmentation
29.06. Assignment H12: Optic Flow
06.07. Assignment H13: Correlation-Based Stereo Method

Sample solutions are only available during the semester.

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, Third Edition, 2008.
  • 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.
General information and numerous links can be found at the Computer Vision Homepage. If you are looking for a specific reference, check out Keith Price's Annotated Computer Vision Bibliography. Many online articles and citations can be extracted from the CiteSeer webpage.

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