Infopage for IP1: Image Processing (Mo. 10-12h & Th. 12-14h)
This lecture forms the foundation to deepen knowlede in the resarch area of ''Image Processing''. All master students, who are interested in this exciting research area of image prcessing and scene analyiss are invited to join this lecture series. This series also provides a perfect basement for the upcoming lectures of image processing 2 (IP2) in the next semester. Since this lecture is a part of the International Master Course Informatics of the University of Hamburg the language used in this course is English. However, oral examinations can be performed in German or English.
The procedure of this course consists of lectures with integrated exercises.
Topics
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Image processing for multimedia applications (~ 4 weeks):
- Introduction
- Digital images and their properties
- Data structures for image processing
- Pre-processing
- Image compression
-
Image analysis (~ 6 weeks):
- Image Segmentation
- Edge-based Segmentation
- Shape decription
- Image morphology
- Texture analysis
- Motion analysis
-
See and act (~ 3 weeks):
- 3D image analysis
- Object recognition
- Scene analyis
- Konwledge-based scene interpretation
Lecture slides
The English lecture slides will be made accessible trough this site on each Monday and Thursday before the lectures.
- Mo 13.10.2014: Introduction
- Th 16.10.2014: Python Introduction
- Mo 20.10.2014: Image Understanding and Image Formation
- Th 23.10.2014: Discussion of exercise 1, Sampling and the frequency domain cont.
- Mo 27.10.2014: Shape-preserving Sampling and Thresholding
- Th 30.10.2014: Discussion of exercise 2, Perspective transformations
- Mo 03.11.2014: Image properties and filters
- Th 06.11.2014: Spectral image processing and convolution
- Mo 10.11.2014: Spectral image processing and convolution cont.
- Th 13.11.2014: Image Compression (1)
- Mo 17.11.2014: Image Compression (2)
- Th 20.11.2014: Discussion of exercise 3
- Mo 24.11.2014: Image Segmentation (1)
- Th 27.11.2014: Image Segmentation (2)
- Mo 1.12.2014: Discussion of exercise 4
- Th 4.12.2014: Grouping and Searching
- Mo 8.12.2014: Grouping and Shape Features
- Th 11.12.2014: Skeletonization and Matching
- Mo 15.12.2014: Pattern recognition, Project Introduction
- Th 18.12.2014: Decision Theory
- Mo 5.1.2014: Decision Theory cont.
- Th 8.1.2014: Motion Analysis (1)
- Mo 12.1.2014: Motion Analysis (2)
- Th 15.1.2014: Shape from Shading (including Camera Geometry and 3D Image Analysis)
- Mo 19.1.2014: Object Recognition (1)
- Th 22.1.2014: Object Recognition (2)
- Mo 26.1.2014: High Level Vision
- Th 29.1.2014: Project Presentations, A walk through the lecture series
Exercises
The exercises are colocated to the course on a two-weekly cycle, solutions will be discussed in each following week. The exercises consist of five exercise sheets and a small project at the end.
Please send your solutions until Thursday 12 am to Benjamin Seppke.
- 16.10. - 23.10.2014: Getting started
- 23.10. - 30.10.2014: Image formation
- 30.10. - 13.11.2014: Perspective projections
- 13.11. - 27.11.2014: Histograms, Filters, Convolution and Fourier-Transform
- 27.11. - 11.12.2014: Image Compression and Segmentation
- 11.12.2014 - 26.01.2015: Project: Writer identification in historic manuscripts (Project definition, Project dataset)
References
- New recommendation: Richard Szeliski (2010): Computer Vision: Algorithms and Applications (Homepage and eBook download)
- Sonka, Hlaváč und Boyle (3. Auflage 2008): Image Processing, Analysis and Machine Vision, Thomson
- D.A. Forsyth, J. Ponce: Computer Vision, A Modern Approach, Prentice-Hall 2003
- R.C. Gonzalez, R.E. Woods: Digital Image Processing, Prentice-Hall 2001
- B. Jähne (1997): Digitale Bildverarbeitung (4. Auflage), Springer-Verlag
- R. Klette, A. Koschan, K. Schluns (1996): Computer Vision, Vieweg
- R.M. Haralick, L.G. Shapiro (1993): Computer and Robot Vision, Vol. I & II, Addison-Wesley
Additional references will be announced in the course.