Welcome to the homepage of the lecture

Image Processing and Computer Vision

Summer Term 2017

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 2017

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 18, 2017

Tutorials: 2 hours each week; see below.

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

02.08.17: Opportunity for exam inspection:
Friday, August 4, Room 4.10, Building E1 7, 2:00 p.m. - 4:00 p.m.

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

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

24.07.2017: The list of admitted students is online!

21.04.2017:  Registration is closed.

18.04.2017:  Registration starts on Tuesday, April 18, 2017, 2:00 p.m. and ends Friday, April 21, 2017, 2:00 p.m.

18.04.2017:  Registration is opened!

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 German)
    Tutor: Aaron Wewior

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

  • Group T3:
    Tue, 16-18, Building E1.3, Seminar Room 014
    (English only)
    Tutor: Jiayi Wang

  • Group W1:
    Wed, 10-12, Building E2.5, Seminar Room 3 (U 11)
    (English only)
    Tutor: Jón Arnar Tómasson

  • Group W2:
    Wed, 14-16, Building E2.5, Seminar Room 4 (U 16)
    Tutor: Tobias Alt

  • Group W3:
    Wed, 16-18, Building E2.5, Seminar Room 4 (U 16)
    (English only)
    Tutor: Jón Arnar Tómasson

Remarks: All groups except T1 are conducted in English. Groups marked with "English only" also only accept exercise submissions in English.

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

  • Optional Guided Programming (OGP):
    Tue, 18-20, CIP 012 in Building E1.3
    Tutor: Kireeti Bodduna

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.

Between Tue, April 18, 2017, 14:00 and Fri, April 21, 2017, 14:00, 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
Tuesday, August 1, 2017 from 14:00 to 17:00,
in Building E2.2, Günter Hotz Lecture Theatre, and Building E1.3, Lecture Hall 002.

The second written exam takes place on
Friday, October 6, 2017 from 14:00 to 17:00,
in Building E2.2, Günter Hotz Lecture Theatre, and Building E1.3, Lecture Hall 002.

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 Tuesday, August 1, 2017 from 14:00 to 17:00:

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

If you are unsure, in which lecture hall you belong, you can check on this detailed list.

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, August 4, 2017 from 2:00 p.m. to 4:00 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
18.04. Foundations I: Definitions, Image Types, Discretisation
21.04. Foundations II: Degradations in Digital Images
(contains classroom assignment C1 and homework H1)
25.04. Foundations III: Colour Perception and Colour Spaces
28.04. Image Transformations I: Continuous Fourier Transform
(contains classroom assignment C2 and homework H2)
02.05. Image Transformations II: Sampling Theorem and Discrete Fourier Transform
05.05. Image Transformations III: Discrete Cosine Transform and Image Pyramids
(contains classroom assignment C3 and homework H3)
09.05. Image Transformations IV: Discrete Wavelet Transform
12.05. Image Compression
(contains classroom assignment C4 and homework H4)
16.05. Image Interpolation


Date Topic
19.05. Point Operations
(contains classroom assignment C5 and homework H5)
23.05. Linear Filters I: System Theory
26.05. Linear Filters II: Derivative Filters
(contains classroom assignment C6 and homework H6)
30.05. Linear Filters III: Detection of Edges and Corners
02.06. Nonlinear Filters I: Morphology and Median Filters
(contains classroom assignment C7 and homework H7)
06.06. Nonlinear Filters II: Wavelet Shrinkage, Bilateral Filters, NL-Means
09.06. Nonlinear Filters III: Nonlinear Diffusion Filtering
(contains classroom assignment C8 and homework H8)
13.06. Global Filters I: Discrete Variational Methods
16.06. Global Filters II: Continuous Variational Methods
(contains classroom assignment C9 and homework H9)
20.06. Global Filters III: Deconvolution Methods
23.06. Texture Analysis
(contains classroom assignment C10 and homework H10)


Date Topic
27.06. Segmentation I: Thresholding, Region Growing, Region Merging
30.06. Segmentation II: Watersheds and Optimisation Methods
(contains classroom assignment C11 and homework H11)
04.07. Image Sequence Analysis I: Local Methods
07.07. Image Sequence Analysis II: Variational Methods
(contains classroom assignment C12 and homework H12)
11.07. 3-D Reconstruction I: Camera Geometry
14.07. 3-D Reconstruction II: Stereo
(contains classroom assignment C13 and homework H13)
18.07. 3-D Reconstruction III: Shape-from-Shading
21.07. Object Recognition I: Hough Transform and Invariants
25.07. Object Recognition II: Eigenspace Methods
28.07. 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.

21.07. Self Test Problem Sheet
21.07. Self Test Solution

Here you can download material for the programming assignments.

21.04. Assignment H1: Noise, Quantisation, and Dithering
28.04. Assignment H2: Colour Spaces and Subsampling
05.05. Assignment H3: Fourier Analysis and Fourier Filtering
12.05. Assignment H4: Discrete Cosine Transform
19.05. Assignment H5: Point Transformations
26.05. Assignment H6: Linear Filters
02.06. Assignment H7: Edge and Corner Detection, Morphology
09.06. Assignment H8: Wavelet Shrinkage, NL-Means
16.06. Assignment H9: Whittaker-Tikhonov Regularisation, Unsharp Masking
23.06. Assignment H10: Texture Inpainting, Deconvolution
30.06. Assignment H11: Toboggan Watershed Segmentation
07.07. Assignment H12: Optic Flow
14.07. Assignment H13: Correlation-Based Stereo Method

Here you find example solutions for the assignments.

28.04. Assignment C1: Convolution, Box-Muller Algorithm
28.04. Assignment H1: PSNR, Convolution, Noise, Quantisation and Dithering
05.05. Assignment C2: Colour Spaces, Continuous Fourier Transform
05.05. Assignment H2: Continuous Fourier Transform, Colour Spaces
12.05. Assignment C3: Fourier Spectrum, Image Pyramids
12.05. Assignment H3: Discrete Fourier Transform,
Fourier Spectrum, Fourier Filtering
19.05. Assignment C4: Discrete Wavelet Transform
19.05. Assignment H4: Transformation Matrices, DFT and DWT,
Huffman Coding
26.05. Assignment C5: Point Operations
26.05. Assignment H5: Keys Interpolation, B-Spline Interpolation,
Affine Rescaling, Gamma Correction, Histogram Equalisation
02.06. Assignment C6: Linear Filters, Derivative Filters
02.06. Assignment H6: Derivative Approximation, Fourier Analysis,
Linear Filters
09.06. Assignment C7: Tensor Analysis, Mean and Median Filtering
09.06. Assignment H7: Structure Tensor Analysis,
Morphology, Edge and Corner Detection
16.06. Assignment C8: Bilateral Filtering and NL-Means
16.06. Assignment H8: Multiple Choice, Nonlinear Diffusion,
Wavelet Shrinkage, NL-Means
23.06. Assignment C9: Convexity of a Discrete Energy Function,
Euler-Lagrange Equations
23.06. Assignment H9: Variational Methods, Fourier Analysis of Linear
Filters, Whittaker-Tikhonov Regularisation, Unsharp Masking
30.06. Assignment C10: Cooccurrence Matrices, Inverse Filtering
30.06. Assignment H10: Deconvolution, Texture Inpainting
07.07. Assignment C11: Otsu's Threshold Selection Method,
Toboggan Watershed Algorithm
07.07. Assignment H11: Segmentation Methods, Mumford-Shah
Cartoon Model, Region Merging, Toboggan Watershed Segmentation
14.07. Assignment C12: Optic Flow Constraint
14.07. Assignment H12: Lucas and Kanade, Variational Optic Flow
21.07. Assignment C13: Homogeneous Coordinates, Rotation
21.07. Assignment H13: Transformation Matrices, Fundamental Matrix,
Stereo Reconstruction, Correlation-Based Stereo Method

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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