Welcome to the homepage of the lecture

Image Processing and Computer Vision

Summer Term 2015

Image Processing and Computer Vision

Prof. Joachim Weickert
Office hour: Tuesday, 14:15 - 15:15.

Coordinator of tutorials: Sarah Schäffer
Office hour: Thursday, 14:15 - 15:15.

Summer Term 2015

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

Lectures:
Tuesday, 10-12 c.t., Building E2.2, Günter Hotz Lecture Theatre
Thursday, 10-12 c.t., Building E1.3, Lecture Hall 002

First lecture: Tuesday, April 21, 2015

Tutorials: 2 hours each week; see below.


NEWS: The list of admitted students is online!

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

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

NEWS: Opportunity for exam inspection:
Thursday, August 13, Room 4.10, Building E1 7
Students A - I: 1:30 p.m. - 2:30 p.m.
Students J - Z: 2:30 p.m. - 3:30 p.m.

NEWS: THE SECOND EXAM WILL BE A CLOSED BOOK EXAM.
Check out the exam section for further information.

NEWS: The results of the second written exam are now online.

NEWS: Opportunity for exam inspection:
Thursday, October 15, Room 4.10, Building E1 7
Students A - L: 2 p.m. - 3 p.m.
Students M - Z: 3 p.m. - 4 p.m.



Type of LecturesPrerequisitesTutorialsRegistrationWritten 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 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 Sarah Schäffer.

Seven groups are scheduled for Tuesday and Wednesday afternoon:

  • Group T1:
    Tue, 14-16, Building E1.3, Seminar Room 107
    Tutor: Markus Schneider

  • Group T2:
    Tue, 14-16, Building E1.1, Room U12
    (English only)
    Tutor: Nikita Vedeneev

  • Group T3:
    Tue, 16-18, Building E1.3, Seminar Room 107
    Tutor: Markus Schneider

  • Group T4:
    Tue, 16-18, Building E1.3, Seminar Room 015
    (English only)
    Tutor: Sinan Bozca

  • Group W1:
    Wed, 12-14, Building E1.1, Seminar Room U12
    (in German)
    Tutor: Damaris Gatzsche

  • Group W2:
    Wed, 14-16, Building E1.1, Seminar Room U12
    Tutor: Aaron Wewior

  • Group W3:
    Wed, 16-18, Building E1.1, Seminar Room U12
    Tutor: Aaron Wewior

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: Sinan Bozca

The tutors can be reached via the mail addresses:
ipcv-# -- at -- mia.uni-saarland.de
where # has to be replaced by t1, t2, t3, t4, w1, w2, and w3, respectively.


Between Tue, April 21, 2015, 15:00 and Fri, April 24, 2015, 15:00, 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. You can withdraw your registration until two weeks before the first exam. If you are a junior or Erasmus student, you do not have to register via HISPOS.


The first written exam takes place on
Wednesday, August 5, 2015 from 14:00 to 17:00,
in Building E2.2, Günter Hotz Lecture Theatre, and Building E1.3, Lecture Halls 001-003.

The second written exam takes place on
Monday, October 12, 2015 from 14:00 to 17:00,
in Building E2.2, Günter Hotz Lecture Theatre, and Building E1.3, Lecture Halls 001-003.

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.

Please check here whether you are admitted to the written exam. If you think that there is an error, please contact Sarah Schäffer immediately.

Here is the distribution of places by family name (i.e. surname, last name) for the first exam that takes place on Wednesday, August 5, 2015 from 14:00 to 17:00:

Students Ada - Mat: Building E2.2, Günter Hotz Lecture Theatre
Students Mau - Pal: Building E1.3, Lecture Hall 001
Students Pam - Ste: Building E1.3, Lecture Hall 002
Students Str - Zha: Building E1.3, Lecture Hall 003

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

The second exam is a closed book exam. These are the new rules:

  • You are allowed and obliged to bring two things to your desk only: Your student ID card (Studierendenausweis) and a ball-pen that has no function other than writing. 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, 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 this semester, regardless of what you achieved in the first exam.
  • 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 Thursday, August 13, 2015 in the following timeslots, depending on your last (family) name:
Students A - I: 1:30 p.m. - 2:30 p.m.
Students J - Z: 2:30 p.m. - 3:30 p.m.

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 first written exam has the opportunity to inspect his/her graded solutions in room 4.10 in Building E1.7 Thursday, October 15, 2015 in the following timeslots, depending on your last (family) name:
Students A - L: 2 p.m. - 3 p.m.
Students M - Z: 3 p.m. - 4 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.

PART I: FOUNDATIONS AND TRANSFORMATIONS

Date Topic
21.04. Foundations I: Definitions, Image Types, Discretisation
23.04. Foundations II: Degradations in Digital Images
(contains classroom assignment C1 and homework H1)
28.04. Foundations III: Colour Perception and Colour Spaces
30.04. Image Transformations I: Continuous Fourier Transform
(contains classroom assignment C2 and homework H2)
05.05. Image Transformations II: Sampling Theorem and Discrete Fourier Transform
07.05. Image Transformations III: Discrete Cosine Transform and Image Pyramids
(contains classroom assignment C3 and homework H3)
12.05. Image Transformations IV: Discrete Wavelet Transform
13.05. Image Compression
(contains classroom assignment C4 and homework H4)
Shifted to Wednesday, May 13, 6:15-8:00 p.m., E1.3, Lecture Hall 2.
19.05. Image Interpolation

PART II: IMAGE PROCESSING

Date Topic
21.05. Point Operations
(contains classroom assignment C5 and homework H5)
26.05. Linear Filters I: System Theory
28.05. Linear Filters II: Derivative Filters
(contains classroom assignment C6 and homework H6)
02.06. Linear Filters III: Detection of Edges and Corners
03.06. Nonlinear Filters I: Morphology and Median Filters
(contains classroom assignment C7 and homework H7)
Shifted to Wednesday, June 3, 6:15-8:00 p.m., E1.3, Lecture Hall 2.
09.06. Nonlinear Filters II: Wavelet Shrinkage, Bilateral Filters, NL-Means
11.06. Nonlinear Filters III: Nonlinear Diffusion Filtering
(contains classroom assignment C8 and homework H8)
16.06. Global Filters I: Discrete Variational Methods
18.06. Global Filters II: Continuous Variational Methods
(contains classroom assignment C9 and homework H9)
23.06. Global Filters III: Deconvolution Methods
25.06. Texture Analysis
(contains classroom assignment C10 and homework H10)

PART III: COMPUTER VISION AND IMAGE UNDERSTANDING

Date Topic
30.06. Segmentation I: Thresholding, Region Growing, Region Merging
02.07. Segmentation II: Watersheds and Optimisation Methods
(contains classroom assignment C11 and homework H11)
07.07. Image Sequence Analysis I: Local Methods
09.07. Image Sequence Analysis II: Variational Methods
(contains classroom assignment C12 and homework H12)
14.07. 3-D Reconstruction I: Camera Geometry
16.07. 3-D Reconstruction II: Stereo
(contains classroom assignment C13 and homework H13)
21.07. 3-D Reconstruction III: Shape-from-Shading
23.07. Object Recognition I: Hough Transform and Invariants
28.07. Object Recognition II: Eigenspace Methods
30.07. 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.

DateTopic
23.07. Self Test Problem Sheet


Here you can download material for the programming assignments.

DateTopic
23.04. Assignment H1: Noise, Quantisation and Dithering
30.04. Assignment H2: Colour Spaces and Subsampling
07.05. Assignment H3: Fourier Analysis and Fourier Filtering
13.05. Assignment H4: Discrete Cosine Transform
21.05. Assignment H5: Point Transformations
28.05. Assignment H6: Linear Filters
03.06. Assignment H7: Edge and Corner Detection, Morphology
11.06. Assignment H8: Wavelet Shrinkage, NL-Means
18.06. Assignment H9: Whittaker-Tikhonov Regularisation, Unsharp Masking
25.06. Assignment H10: Texture Inpainting, Deconvolution
02.07. Assignment H11: Toboggan Watershed Segmentation
09.07. Assignment H12: Optic Flow
14.07. Assignment H13: Correlation-Based Stereo Method

Sample solutions are only available during the semester.

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

  • E. Trucco, A. Verri: Introductory Techniques for 3-D Computer Vision. Prentice Hill, Upper Saddle River, 1998.
  • R. Klette: Concise Computer Vision. Springer, London, 2014.
  • R. Szeliski: Computer Vision: Algorithms and Applications. Springer, New York, 2010.

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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