Welcome to the homepage of the lecture

Image Processing and Computer Vision

Winter term 2005 / 2006

Image Processing and Computer Vision

Prof. Joachim Weickert

Winter term 2005 / 2006

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

Lectures: Tuesday and Thursday, 11-13 c.t., Building E13/45, Lecture Hall 2

First lecture: Tuesday, October 18, 2005

Tutorials: 2 hours each week; see below.

Regulations for the TutorialsPrerequisitesTypes of LecturesTutorialsWritten ExamContentsMaterial for the Programming AssignmentsSolutions to ExercisesSelf-Test ProblemsLiterature

8 groups are scheduled for Tuesday and Wednesday:

  • Group T1: Tue, 14-16,  Bldg. E13/45, room 016 (theory),   Bldg. E24/27.1, CIP-pool U009 (programming)
  • Group T2: Tue, 14-16,  Bldg. E24/27.1, room 012 (theory),   Bldg. E13/45, CIP-pool 012 (programming)
  • Group T4: Tue, 16-18,  Bldg. E13/45, room 016 (theory),   Bldg. E24/27.1, CIP-pool U009 (programming)
  • Group T5: Tue, 16-18,  Bldg. E24/27.1, room 215 (theory),   Bldg. E13/45, CIP-pool 012 (programming)
    The tutorials of group T5 will be held in German.
  • Group W1: Wed,   9-11,  Bldg. E13/45, room 015 (theory),   Bldg. E24/27.1, CIP-pool U009 (programming)
  • Group W2: Wed, 11-13,  Bldg. E13/45, room 014 (theory),   Bldg. E24/27.1, CIP-pool U009 (programming)
  • Group W4: Wed, 14-16,  Bldg. E13/45, room 014 (theory),   Bldg. E24/27.1, CIP-pool U009 (programming)
    also honours programme (Förderstudierende)
  • Group W5: Wed, 16-18,  Bldg. E24/27.1, room 012 (theory),   Bldg. E24/27.1, CIP-pool U009 (programming)

You could enroll for a tutorial from Wed, Oct. 19, 2005, 23:00h until Sun, Oct. 23, 2005, 23:00h.
Tuesday groups start on October 25, Wednesday groups on October 26.

This course is suitable for students of mathematics or computer science. It counts either as a theoretical core course (Theorie-Stammvorlesung) in computer science or as an applied mathematics course. 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.

Broad introduction into 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 thesis in our group.
The lectures are continued in the summer term by the in-depth course "Differential Equations in Image Processing and Computer Vision" which leads to current research topics. Both classes are necessary in order to pursue a diploma or master thesis in our group.

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. The tutorials are conducted by Andrés Bruhn, Mahmoud Fouz, Christian Schmaltz, Ellen Schmeyer, and Oliver Vogel.

The written exam took place on February 21, 2006 at 2 PM.
A second exam will be offered on April 7, 2006 at 2 PM (until 5 PM).

NEWS: All students have the opportunity to improve their mark from the first exam in the second one. Only the BETTER mark counts.

Here is the distribution of places for the second exam:

Students ALBESSER - KAHL go to the MATH I lecture hall in building E2.5
Students KAISER - NGUYEN : MATH II lecture hall
Students NIKOLOVA - SCHEFER : MATH III lecture hall
Students SCHERBAUM - ZUKOWSKI : Computer Science building E13, lecture hall 2

Please do not forget to bring your student ID card with you.

The following thresholds were applied in determining the grades:

  • grade 1.0 : 56 - 64 points
  • 1.3 : 53 - 55
  • 1.7 : 51 - 52
  • 2.0 : 48 - 50
  • 2.3 : 46 - 47
  • 2.7 : 43 - 45
  • 3.0 : 41 - 42
  • 3.3 : 38 - 40
  • 3.7 : 35 - 37
  • 4.0 : 32 - 34
  • 5.0 : 0 - 31

The detailed distribution of points and marks can be found here.

The results can be queried via our online query form.

You could inspect your exam sheets on Friday, March 10,
building E1.1, room 3.06 (3rd floor).
The time depended on your last name:
A - H : 1 pm - 2 pm
I - P : 2 pm - 3 pm
Q - Z : 3 pm - 4 pm

Please note that the material on this webpage is made available to support the classroom teaching and the tutorials, not to replace them. Additional organisational informations, 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.

18. 10. Definitions, Image Types, Discretisation
20. 10. Degradations in Digital Images
25. 10. Image Transformations I: Continuous Fourier Transform
27. 10. Image Transformations II: Discrete Fourier Transform
3. 11. Image Transformations III: Image Pyramids
8. 11. Image Transformations IV: Wavelets
10. 11. Colour Perception and Colour Spaces
15. 11. Image Enhancement I: Point Operations
17. 11. Image Enhancement II: Linear Filtering
22. 11. Image Enhancement III: Wavelet Shrinkage, Median Filtering, M-Smoothers
24. 11. Image Enhancement IV: Mathematical Morphology
29. 11. Image Enhancement V: Diffusion Filtering
1. 12. Image Enhancement VI: Discrete Variational Methods
6. 12. Image Enhancement VII: Continuous Variational Methods
8. 12. Image Enhancement VIII: Fourier Methods and Deconvolution
13. 12. Image Interpolation
15. 12. Feature Extraction I: Edges
20. 12. Feature Extraction II: Corners
22. 12. Feature Extraction III: Hough Transform
10. 1. Texture Analysis
12. 1. Segmentation I: Classical Methods
17. 1. Segmentation II: Optimisation Methods
19. 1. Image Sequence Analysis I: Local Methods
24. 1. Image Sequence Analysis II: Variational Methods
26. 1. 3D Reconstruction I: Camera Geometry
31. 1. 3-D Reconstruction II: Stereo Reconstruction
2. 2. 3-D Reconstruction III: Shape-from-Shading
7. 2. Object Recognition I: Moment Invariances
9. 2. Object Recognition II: Eigenspace Methods
14. 2. Image Compression
16. 2. Summary, Conclusions, Outlook

27. 10. Assignment P1: Fourier Transform
15. 11. Assignment P2: Point Operations
29. 11. Assignment P3: Mathematical Morphology
13. 12. Assignment P4: Deconvolution
10. 01. Assignment P5: Edges and Corners
24. 01. Assignment P6: Optic Flow
07. 02. Assignment P7: Stereo

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

  • R. C. Gonzalez, R. E. Woods: Digital Image Processing. Addison-Wesley, Second Edition, 2002.
  • K. D. Tönnies: Grundlagen der Bildverarbeitung. Pearson Studium, München, 2005.
  • K. R. Castleman: Digital Image Processing. Prentice Hall, Englewood Cliffs, 1996.

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 computer science library.
Furthermore, there is an interesting online compendium, where many researchers have written survey articles.
General informations 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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