Welcome to the homepage of the lecture

Image Processing and Computer Vision

Winter term 2009 / 2010

Image Processing and Computer Vision

Prof. Joachim Weickert
Office hours: Friday, 14:15 - 15:15.

Coordinator of tutorials: Markus Mainberger

Winter Term 2009 / 2010

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

Lectures: Tuesday and Thursday, 10-12 c.t., Building E1.3, Lecture Hall 002

First lecture: Tuesday, October 13, 2009

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, 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 (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. If you miss a tutorial partially, you will lose the points that correspond the proportion of missed time. 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 Peter Ochs, Peter Geber, Pengming Wang, Pascal Peter and Kai Hagenburg.

Seven groups are scheduled from Tuesday to Thursday:

  • Group T1 (Peter Ochs):
    Tue, 12 am - 2 pm, Bldg. E2.5, seminar room 1 (H05)
  • Group T2 (Pengming Wang):
    Tue, 4 pm - 6 pm, Bldg. E2.4, seminar room 10 (012)
  • Group T3 (Pascal Peter):
    Tue, 4 pm - 6 pm, Bldg. E2.5, lecture hall III, in German
  • Group W1 (Peter Ochs):
    Wed, 10 am - 12 am, Bldg. E1.3, seminar room 014
  • Group W2 (Pascal Peter):
    Wed, 2 pm - 4 pm, Bldg. E1.3, seminar room 014, also honours programme (Förderstudierende)
  • Group T4 (Peter Geber):
    Thu, 2 pm - 4 pm, Bldg. E2.5, seminar room 2 (H04)
  • Group T5 (Peter Geber):
    Thu, 4 pm - 6 pm, Bldg. E2.5, seminar room 2 (H04)

  • Optional Guided Programming (OGP) (Kai Hagenburg):
    Tue, 6 pm - 8 pm, 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, t4, t5 and ogp respectively.

Registration: Registration is closed. It was open from Tue, Oct. 13, 2009, 3 pm until Fri, Oct. 16, 2009, 3 pm. You can now check which group you are finally in.

The first written exam took place on
Tuesday, February 09, 2010 from 2:00 to 5:00 pm,
in building E 2.5, lecture hall I-III

The second written exam took place on
Tuesday, April 06, 2010 from 2:00 to 5:00 pm,
in building E 2.5, lecture hall I-III.

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 course material (including lecture notes and example solutions from this web page) and hand-written notes, but neither books nor any other printed material.
  • 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.
  • Solutions that are written with pencil will not be graded.

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 25th, 2010, 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 Tuesday, April 13th, 2010, 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
13.10. Foundations I: Definitions, Image Types, Discretisation
15.10. Foundations II: Degradations in Digital Images
(contains classroom assignment C1 and homework H1)
20.10. Foundations III: Colour Perception and Colour Spaces
22.10. Image Transformations I: Continuous Fourier Transform
(contains classroom assignment C2 and homework H2)
27.10. Image Transformations II: Sampling Theorem and Discrete Fourier Transform
29.10. Image Transformations III: Discrete Cosine Transform and Image Pyramids
(contains classroom assignment C3 and homework H3)
03.11. Image Transformations IV: Discrete Wavelet Transform
05.11. Image Compression
(contains classroom assignment C4 and homework H4)
10.11. Image Interpolation


Date Topic
12.11. Point Operations
(contains classroom assignment C5 and homework H5)
17.11. Linear Filters I: System Theory
19.11. Linear Filters II: Edge Detection
(contains classroom assignment C6 and homework H6)
24.11. Linear Filters III: Multichannel Edges, Corners
26.11. Nonlinear Filters I: Morphology and Median Filters
(contains classroom assignment C7 and homework H7)
01.12. Nonlinear Filters II: Wavelet Shrinkage, Bilateral Filters, NL-Means
03.12. Nonlinear Filters III: Nonlinear Diffusion Filtering
(contains classroom assignment C8 and homework H8)
08.12. Global Filters I: Discrete Variational Methods
10.12. Global Filters II: Continuous Variational Methods
(contains classroom assignment C9 and homework H9)
15.12. Global Filters III: Deconvolution Methods
17.12. Texture Analysis
(contains classroom assignment C10 and homework H10)


Date Topic
05.01. Segmentation I: Classical Methods
07.01. Segmentation II: Optimisation Methods
(contains classroom assignment C11 and homework H11)
12.01. Image Sequence Analysis I: Local Methods
14.01. Image Sequence Analysis II: Variational Methods
(contains classroom assignment C12 and homework H12)
19.01. 3-D Reconstruction I: Camera Geometry
21.01. 3-D Reconstruction II: Stereo
(contains classroom assignment C13 and homework H13)
26.01. 3-D Reconstruction III: Shape-from-Shading
28.01. Object Recognition I: Hough Transform and Invariants
02.02. Object Recognition II: Eigenspace Methods
04.02. Summary, Conclusions, Outlook

Here you can download material for the programming assignments.

15. 10. Assignment H1: Noise, Quantisation and Dithering
22. 10. Assignment H2: Colour Spaces and Subsampling
29. 10. Assignment H3: Fourier Analysis and Discrete Cosine Transform
05. 11. Assignment H4: Bitplanes
12. 11. Assignment H5: Point Transformations
19. 11. Assignment H6: Canny Edge Detector
26. 11. Assignment H7: Morphology
03. 12. Assignment H8: NL-Means
10. 12. Assignment H9: Whittaker-Tikhonov Regularisation, Unsharp Masking
17. 12. Assignment H10: Deconvolution
07. 01. Assignment H11: Toboggan Watershed Segmentation
14. 01. Assignment H12: Optic Flow
21. 01. Assignment H13: Correlation-Based Stereo Method

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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