Welcome to the homepage of the lecture

Image Processing and Computer Vision

Winter term 2006 / 2007

Image Processing and Computer Vision

Dr. Bernhard Burgeth

Winter term 2006 / 2007

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

Lectures: Tuesday and Thursday, 11-13 c.t., Building E13, Lecture Hall 002

First lecture: Tuesday, October 17, 2006

Tutorials: 2 hours each week; see below.

Breaking News:
Opportunity for exam inspection: Thursday, March 29, 14:00 - 15:00, Room 3.06, Bld. E1 1
Results of the second written exam

TutorialsPrerequisitesTypes of LecturesTutorialsWritten ExamContentsMaterial for the Programming AssignmentsLiterature

6 groups are scheduled for Tuesday, Wednesday and Thursday:

  • Group T1: Tue, 16-18,  also honours programme (Förderstudierende)
    Bldg. E2 4, seminar room 5 (theory); Bldg. E1 3, CIP 105 (programming)
  • Group W1: Wed, 11-13
    Bldg. E2 4, seminar room 5 (theory); Bldg. E1 3, CIP 012 (programming)
  • Group W2: Wed, 11-13,  in German
    Bldg. E1 1, seminar room U (Untergeschoß) (theory); Bldg. E1 3, CIP 105 (programming)
  • Group W3: Wed, 14-16
    Bldg. E1 1, seminar room U (Untergeschoß) (theory); Bldg. E1 3, CIP012 (programming)
  • Group W4: Wed, 14-16,  in German
    Bldg. E2 5, seminar room 2 (theory); Bldg. E1 3, CIP105 (programming)
  • Group T2: Thu, 9-11
    Bldg. E2 5, Zeichensaal (theory); Bldg. E1 3, CIP012 (programming)

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. If you have questions concerning the tutorials, please do not hesitate to contact Stephan Didas. The tutorials are conducted by Mohamed Abdelmaksoud, Marin Katov, Christian Morbach, and Verena Schmitt.

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. A list with the student id numbers of all students qualified for the exams can be found at the information board next to the entrance of our work group. In the lecture on Tuesday, February 13, you will also have the opportunity to check if you are on our list for the exam. In case of qualification, you are allowed to take part in both exams. Only the better grade counts.
There are several 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.
  • A non-programmable pocket calculator is required.
  • 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 first written exam has taken place on Friday, February 23, 2007, from 2 PM to 5 PM.
The second exam has taken place on Wednesday, March 21, 2007 at 2 PM (until 5 PM).

The student ID numbers of all students who qualified for taking part in the exams can be found on the notice-board next to the entrance of the MIA group in building E1 1.

Those who will not take part in the final exam have had the opportunity to unregister from the lecture until Thursday, February 8th, 2007.

The results of the second written exam can be found here, and the corresponding distribution of points and grades here.
The distribution of points and grades of the first exam can be found here.

Each student who has participated in the second written exam has the opportunity to to inspect his/her graded solutions in room 3.06 in Bldg. E1 1 on Thursday, March 29th, 2007, from 2:00 P.M. to 3:00 P.M.

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 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.

Date Topic
17.10. Definitions, Image Types, Discretisation
19.10. Degradations in Digital Images
24.10. Image Transformations I: Continuous Fourier Transform (T1, P1)
26.10. Image Transformations II: Discrete Fourier Transform
31.10. Image Transformations III: Image Pyramids (T2)
2.11. Image Transformations IV: The Discrete Wavelet Transform
7.11. Color Perception and Color Spaces (P2)
9.11. Image Enhancement I: Point Operations
14.11. Image Enhancement II: Linear Filters (T3)
16.11. Image Enhancement III: Wavelet Shrinkage, Median Filters, M-Smoothers
21.11. Image Enhancement IV: Morphological Filters (P3)
23.11. Image Enhancement V: Nonlinear Diffusion Filtering
28.11. Image Enhancement VI: Discrete Variational Methods (T4)
30.11. Image Enhancement VII: Continuous Variational Methods
05.12. Image Enhancement VIII: Fourier Methods and Deconvolution (P4)
07.12. Image Interpolation
12.12. Feature Extraction I: Edges (T5)
14.12. Feature Extraction II: Edges in Multichannel Images and Corners
19.12. Feature Extraction III: Contour Representations and Hough Transform (P5)
21.12. Texture Analysis
09.01. Segmentation I: Classical Methods (T6)
11.01. Segmentation II: Optimisation Methods
16.01. Image Sequence Analysis I: Local Methods (P6)
18.01. Image Sequence Analysis II: Variational Methods
23.01. 3-D Reconstruction I: Camera Geometry (T7)
25.01. 3-D Reconstruction II: Stereo
30.01. 3-D Reconstruction III: Shape-from-Shading (P7)
01.02. Object Recognition I: Moment Invariants
06.02. Object Recognition II: Eigenspace Methods (Self Test)
08.02. Image Compression
13.02. Summary, Conclusions, Outlook

24. 10. Assignment P1: Representing Images and Noise Generation
07. 11. Assignment P2: Discrete Fourier Transform
21. 11. Assignment P3: Point Transformations
05. 12. Assignment P4: Morphological Operations
19. 12. Assignment P5: Deconvolution and Edge Detection
11. 01. Assignment P6: Double Thresholding
30. 01. Assignment P7: Optic Flow

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, Second Edition, 2002.
  • 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 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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