Welcome to the homepage of the lecture

Image Processing and Computer Vision

Winter term 2008 / 2009

Image Processing and Computer Vision

Prof. Joachim Weickert
(Building E1.1, Room 3.11, Phone 0681-302-57340)

Winter term 2008 / 2009

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

Lectures: Tuesday and Thursday, 10-12 c.t., Building E13, Lecture Hall 002

First lecture: Tuesday, October 21, 2008

Tutorials: 2 hours each week; see below.

NEWS: The certificates are ready and can be fetched in room 111, building E2.4 (Geschaeftszimmer Mathematik, Frau Voss, opening hours for certificates: Mon-Thu 9.00-11.30 am).

Types of LecturesPrerequisitesTutorialsWritten ExamContents Material for the Programming Assignments Literature

Broad introduction to mathematically well-founded areas of image processing and computer vision. These fields are important in numerous applications including medical imaging, computer-aided quality control, robotics, computer graphics, multimedia and artificial intelligence. The classes qualify for starting a bachelor's thesis in our group.
The lectures are continued in the summer term by the course "Differential Equations in Image Processing and Computer Vision" which leads to current research topics. Both classes are necessary in order to pursue a master's thesis in our group.

This course is suitable for students of visual computing, mathematics or computer science. It counts either as a visual computing core course within the visual computing programme, an applied mathematics course within mathematics, or a (theoretical) core course (Theorie-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 programming and theoretical 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. There is no compulsory attendance for the tutorials. However, missing a tutorial results in losing 50% of the possible score of the latest assignment. Working in groups of up to 3 people is permitted, but all persons must be in the same tutorial group.
If you have questions concerning the tutorials, please do not hesitate to contact Markus Mainberger. The tutorials are conducted by Oliver Demetz, Verena Marold, Markus Mainberger, Pascal Peter, Luis Pizarro, and Sebastian Volz.

Six groups are scheduled for Tuesday and Wednesday:

  • Group T1 (Sebastian Volz):
    Tue, 14-16, Bldg. E2.5, Zeichensaal H07
  • Group T2 (Luis Pizarro):
    Tue, 16-18, Bldg. E1.3, seminar room SR15
  • Group T3 (Verena Marold):
    Tue, 16-18, Bldg. E2.5, Zeichensaal H07, in German
  • Group W1 (Oliver Demetz):
    Wed, 08-10, Bldg. E2.5, Zeichensaal H07
  • Group W2 (Oliver Demetz):
    Wed, 10-12, Bldg. E1.4 (MPI), room 023, also honours programme (Förderstudierende)
  • Group W3 (Pascal Peter):
    Wed, 16-18, Bldg. E2.5, lecture hall III
    Exception on 05.11. and 17.12.: Bldg. E1.1, seminar room 306

  • Optional Guided Programming (Markus Mainberger):
    Tue, 18-20, Bldg. E1.3, CIP 012

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.

Registration: Registration is closed. It was open from Tue, Oct. 21, 2008, 15:00h until Fri, Oct. 24, 2008, 15:00h. You can now check which group you are finally in.

The first written exam has taken place on
Tuesday, February 17, 2009 from 2:00 to 5:00 pm,
in building E 2 5, lecture hall I-III

The second written exam has taken place on
Wednesday, April 8, 2009 from 2:00 to 5:00 pm,
in building E 2 5, lecture hall I and II.

In order to qualify for the exams you need 50% of all points from the assignments. Theoretical and practical assignments count for the final score. In case of qualification, you are allowed to take part in both exams. The better grade counts.

These are the rules during the exams:

  • For the exams, you can use the IPCV course material (including lecture notes and example solutions from this web page) and hand-written tutorial notes, but no books.
  • Pocket calculators are not allowed.
  • Mobile phones, PDAs, laptops and other electronic devices have to be turned off.
  • Please keep the student ID card ready for an attendance check during the exam.

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 had the opportunity to inspect his/her graded solutions in room 3.06 in Bldg. E1.1 on Thursday, February 26th, 2009, from 2:15 pm to 4:15 pm

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 had the opportunity to inspect his/her graded solutions in room 3.06 in Bldg. E1.1 on Wednesday, April 15th, 2009, from 4:15 pm to 6:15 pm

Course material will be made 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
21.10. Foundations I: Definitions, Image Types, Discretisation
23.10. Foundations II: Degradations in Digital Images
(contains classroom assignment C1 and homework H1)
28.10. Foundations III: Colour Perception and Colour Spaces
30.10. Image Transformations I: Continuous Fourier Transform
(contains classroom assignment C2 and homework H2)
04.11. Image Transformations II: Discrete Fourier Transform
06.11. Image Transformations III: Image Pyramids
(contains classroom assignment C3 and homework H3)
11.11. Image Transformations IV: The Discrete Wavelet Transform
13.11. Image Compression
(contains classroom assignment C4 and homework H4)
18.11. Image Interpolation


Date Topic
20.11. Point Operations
(contains classroom assignment C5 and homework H5)
25.11. Linear Filters I: System Theory
27.11. Linear Filters II: Edge Detection
(contains classroom assignment C6 and homework H6)
02.12. Linear Filters III: Multichannel Edges, Corners
04.12. Nonlinear Filters I: Morphology and Median Filters
(contains classroom assignment C7 and homework H7)
09.12. Nonlinear Filters II: Wavelet Shrinkage, Bilateral Filters, NL-Means
11.12. Nonlinear Filters III: Nonlinear Diffusion Filtering
(contains classroom assignment C8 and homework H8)
16.12. Global Filters I: Discrete Variational Methods
18.12. Global Filters II: Continuous Variational Methods
(contains classroom assignment C9 and homework H9)
06.01. Global Filters III: Deconvolution Methods
08.01. Texture Analysis
(contains classroom assignment C10 and homework H10)


Date Topic
13.01. Segmentation I: Classical Methods
15.01. Segmentation II: Optimisation Methods
(contains classroom assignment C11 and homework H11)
20.01. Image Sequence Analysis I: Local Methods
22.01. Image Sequence Analysis II: Variational Methods
(contains classroom assignment C12 and homework H12)
27.01. 3-D Reconstruction I: Camera Geometry
29.01. 3-D Reconstruction II: Stereo
(contains classroom assignment C13 and homework H13)
03.02. 3-D Reconstruction III: Shape-from-Shading
05.02. Object Recognition I: Hough Transform and Invariants
10.02. Object Recognition II: Eigenspace Methods
12.02. Summary, Conclusions, Outlook

23. 10. Assignment H1: Noise Generation and Convolution
30. 10. Assignment H2: Colour Spaces, Fourier Transform
06. 11. Assignment H3: Discrete Cosine Transform
13. 11. Assignment H4: Bitplanes
21. 11. Assignment H5: Point Transformations
02. 12. Assignment H6: Canny Edge Detector
04. 12. Assignment H7: Corner Detection, Morphological Operators
11. 12. Assignment H8: NL-Means, Method Noise
18. 12. Assignment H9: Whittaker-Tikhonov Regularisation, Unsharp Masking
08. 01. Assignment H10: Deconvolution
15. 01. Assignment H11: Double Thresholding
22. 01. Assignment H12: Optic Flow
29. 01. Assignment H13: Correlation-Based Stereo

There is no specific book for this class, but most image processing topics are treated in one of the following books:

  • J. Bigun: Vision with Direction. Springer, Berlin, 2006.
  • R. C. Gonzalez, R. E. Woods: Digital Image Processing. Addison-Wesley, Third Edition, 2008.
  • K. D. Tönnies: Grundlagen der Bildverarbeitung. Pearson Studium, München, 2005.

Specific computer vision books include

  • E. Trucco, A. Verri: Introductory Techniques for 3-D Computer Vision. Prentice Hill, Upper Saddle River, 1998.
  • R. Jain, R. Kasturi, B. G. Schunck: Machine Vision. McGraw-Hill, New York, 1995.
  • R. Klette, K. Schlüns, A. Koschan: Computer Vision: Three-Dimensional Data from Images. Springer, Singapore, 1998.

These and further books can be found in the applied 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. Numerous citations and online articles can be extracted from the CiteSeer webpage.

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