Mathematical Image Analysis Group, Saarland University

Welcome to the homepage of the lecture

Image Processing and Computer Vision

Winter term 2010 / 2011

Image Processing and Computer Vision

Dr. Andrés Bruhn
Office hours: Friday, 14:15 - 15:15.

Coordinator of tutorials: Kai Hagenburg

Winter Term 2010 / 2011

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

Lectures: Tuesday, 2-4 pm c.t. and Thursday, 10-12 am c.t., Building E1.3, Lecture Hall 002

First lecture: Tuesday, October 19, 2010

Tutorials: 2 hours each week; see below.

SECOND EXAM RESULTS ONLINE: The results for the second written exam is online. You can find the individual results at this query page . A histogram of the second exam results can be found here. Opportunity for exam inspection:
Thursday, April 14, 2:00 pm - 4:00 pm, Room 3.06, Bld. E1 1

Types of Lectures – Prerequisites – Tutorials – Written Exam – Contents – Self Test – Material for the Programming Assignments – Example Solutions for the Assignments – Literature

Types of Lectures

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.

Prerequisites

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.

Tutorials

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 Kai Hagenburg. The tutorials are conducted by Sebastian Hoffmann, Rajiv Lund, Ole Rehmsen, Pengming Wang and Kai Hagenburg.

Seven groups are scheduled from Monday to Wednesday:

Group G1 :
Mon, 10 am - 12 am, Bldg. E1.4 (MPI), room 023
Group G2 :
Mon, 12 am - 2 pm, Bldg. E2.4, seminar room 5 (215)
Group G3 :
Mon, 4 pm - 6 pm, Bldg. E2.4, seminar room 5 (215)
Group G4 :
Tue, 10 am - 12 am, Bldg. E1.4 (MPI), room 023
Group G5 :
Wed, 4 pm - 6 pm, Bldg. E2.4, seminar room 3 (216)
Group G6 :
Wed, 4 pm - 6 pm, Bldg. E2.1, seminar room "Süd" (007), in German
Group G7 :
Wed, 6 pm - 8 pm, Bldg. E2.1, seminar room "Süd" (007), also honours programme (Förderstudierende)

Optional Guided Programming (OGP) (Kai Hagenburg):
Tue, 6 pm - 8 pm, Bldg. E1.3, CIP 012

Registration: You can register for this course and enroll for a tutorial between Tue, Oct. 19, 2010, 5 pm and Fri, Oct. 22, 2010, 3 pm

Written Exam:

There will be two written exams:

The first written exam will take place on
Thursday, February 17, 2011 from 2:00 to 5:00 pm,
in building E 2.2, AudiMO and building E 1.3, HS 002

The second written exam will take place on
Thursday, April 07, 2011 from 2:00 to 5:00 pm,
in building E 2.2, AudiMO and building E 1.3, HS 002

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 student ID numbers of all students who qualified for taking part in the exams can be at the notification board of the MIA group.

All students who qualified for taking part in the first exam can also take part in the second exam.

Here is the distribution of places by family name (i.e. surname, last name) for the first exam that takes place on Thursday, February 17, 2011 from 2:00 to 5:00 pm:

Students A - N: AudiMo (new computer science lecture hall), E2.2
Students O - Z: Building E1.3, Lecture hall 002

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

Contents

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.

PART I: FOUNDATIONS AND TRANSFORMATIONS

Date Topic
19.10. Foundations I: Definitions, Image Types, Discretisation

21.10. Foundations II: Degradations in Digital Images

26.10. Foundations III: Colour Perception and Colour Spaces

28.10. Image Transformations I: Continuous Fourier Transform

02.11. Image Transformations II: Sampling Theorem and Discrete Fourier Transform

04.11. Image Transformations III: Discrete Cosine Transform and Image Pyramids

09.11. Image Transformations IV: Discrete Wavelet Transform

11.11. Image Compression

16.11. Image Interpolation

PART II: IMAGE PROCESSING

Date Topic

18.11. Point Operations

23.11. Linear Filters I: System Theory

25.11. Linear Filters II: Edge Detection

30.11. Linear Filters III: Multichannel Edges, Corners

02.12. Nonlinear Filters I: Morphology and Median Filters

07.12. Nonlinear Filters II: Wavelet Shrinkage, Bilateral Filters, NL-Means

09.12. Nonlinear Filters III: Nonlinear Diffusion Filtering

14.12. Global Filters I: Discrete Variational Methods
Attention: Modified since lecture (14.12.)

16.12. Global Filters II: Continuous Variational Methods

04.01. Global Filters III: Deconvolution Methods

06.01. Texture Analysis

PART III: COMPUTER VISION AND IMAGE UNDERSTANDING

Date Topic

11.01. Segmentation I: Classical Methods

13.01. Segmentation II: Optimisation Methods

18.01. Image Sequence Analysis I: Local Methods

20.01. Image Sequence Analysis II: Variational Methods

25.01. 3-D Reconstruction I: Camera Geometry

27.01. 3-D Reconstruction II: Stereo

01.02. 3-D Reconstruction III: Shape-from-Shading

03.02. Object Recognition I: Hough Transform and Invariants

08.02. Object Recognition II: Eigenspace Methods

10.02. Summary, Conclusions, Outlook

Self Test Problems

At the end of the semester there will be a self-test problem sheet which contains 6 problems that are intended to be similar in style and difficulty to a 180-minutes written exam. 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.

Date Topic

01. 02. Self Test Problem Sheet

Material for the Programming Assigments

Here you can download material for the programming assignments.

Submission Date Topic

28. 10. 2010 Assignment H1: Noise, Quantisation and Error Measures

04. 11. 2010 Assignment H2: Colour Spaces and Subsampling

11. 11. 2010 Assignment H3: Fourier Analysis and Discrete Cosine Transform

18. 11. 2010 Assignment H4: Bitplanes

25. 11. 2010 Assignment H5: Point Transformations

02. 12. 2010 Assignment H6: Canny Edge Detector

09. 12. 2010 Assignment H7: Morphology

16. 12. 2010 Assignment H8: NL-Means

06. 01. 2011 Assignment H9: Whittaker-Tikhonov Regularisation, Unsharp Masking

13. 01. 2011 Assignment H10: Deconvolution

20. 01. 2011 Assignment H11: Toboggan Watershed Segmentation

27. 01. 2011 Assignment H12: Optic Flow

03. 02. 2011 Assignment H13: Correlation-Based Stereo Method

Literature

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.