Seminar: Methods and Algorithms for Image Segmentation
SS 09

The Chair of Pattern Recognition and Image Processing offers in SS09 a seminar with the title "Methods and Algorithms for Image Segmentation".

Motivation and Aim:
Segmentation is the partitioning of a digital image into multiple regions, according to some creterion. It builds the threshold between low-level image processing and higher-level analysis and is perhaps the most challenging of all image operations. Depending on the application, image segmentation can base purely on gray values or already make use of prior knowledge about the structures to be segmented.
Diverse approaches to segmentation will be covered in this seminar. you will have a chance to understand the basic ideas behind each approach and to concentrate on one topic and implement the corresponding algorithm. The implementation will be tested on database. Results will be discussed and interpreted.

* During the "Vorsprechung", topics will be bindingly distributed and presentation dates will be fixed.
* An introduction talk on image segmentation will be given in the week following.
* Each participant should give an oral presentation of 45 minutes on his topic.
* The algorithms shall be implemented and tested on database. Results will be discussed and interpreted.

Key information:
Time: Wed. 16:15-17:45
Room: Geb. 106, Multimediaraum (SR 00-007)
Vorbesprechung: Wed. 22.04.2009, 16:15, Geb. 106, SR 00-007
Participants: Students of coumputer science, mathematics, physics or microsystem technology
Language: Talks can be given in German or English
Organisation: Qing Wang (qwang at
Registration: Preregistration in LSF system or per email. Binding registration in the seminar introduction (Wed. 22.04.2009, 16:15, 106-00-007)

Topic Student Betreuer
Image Segmentation with Snakes Based on "Gradient Vector Flow" Qing Wang
Level Sets for Image Segmentation Robert Bensch
Application of Edge Detection and Following in Image Segmentation Thorsten Schmidt
Edge Analysis with Anisotropic Diffusion Wan Nural Jawahir
Detection of Elliptical Objects with Hough Transform Nikos Canterakis
Morphology- and Threshold-based Approach Qing Wang
Image Segmentation Based on Gabor Filters Henrik Skibbe
Density-based segmentation with EM Alexandra Teynor
Invariants-based segmentation Margret Keuper
Segmentation with Markov-Field Maja Temerinac
GrabCut Olaf Ronneberger

Seminar Wiki
To Seminar Wiki

Pollen Data

[1]  C. Xu and J. L. Prince, "Snakes, Shapes, and Gradient Vector Flow", IEEE Transactions on Image Processing, 7(3) March 1998, pp 359-369.
[2]  S.K. Weeratunga and C. Kamath, "An Investigation of Implicit Active Contours for Scientific Image Segmentation", Section 2, 2003. (pdf)
[3]  J. Canny, "A computational approach to edge detection", IEEE PAMI, Vol.8, No.6 (Nov. 1986) pp 679-698.
[4]  Bakalexis, S.A.; Boutalis, Y.S.; Mertzios, B.G., "Edge detection and image segmentation based on nonlinear anisotropic diffusion," Digital Signal Processing, 2002. DSP 2002. 2002 14th International Conference on , vol.2, no., pp. 1203-1206 vol.2, 2002
[5]  K. Kanatani and N. Ohta. "Automatic Detection of Circular Objects by Ellipse Growing", 9th Symposium on Sensing via Image Information (SSII2002), July 2002, Yokohama, Japan, pp. 355-360.
[6]  Rafael C. Gonzalez, Richard E. Woods. Digital Image Processing, Addition-Wesley Publishing Company, 1993.
[7]  A. Jain and F. Farrokhnia, "Unsupervised texture segmentation using Gabor filters", IEEE International Conference on Systems, Man and Cybernetics, 1990. Conference Proceedings.
[8]  C. Carson et al.: Image Segmentation using Expectation Maximization and its application to image querying, TPAMI 24, 2002 Vol.8 pp. 1026-1038
[9]  J. Fehr, O. Ronneberger, H. Kurz, H. Burkhardt, "Self-Learning Segmentation and Classification of Cell-Nuclei in 3D Volumetric Data using Voxel-Wise Gray Scale Invariants", In Proceedings of the 27th DAGM Symposium, in number 3663 LNCS, Springer, Vienna, Austria, 30.8 - 2.9. 2005
[10]  Hongdong Li, Chunhua Shen, Object-Respecting Color Image Segmentation, Image Processing, 2007. ICIP 2007. IEEE International Conference on Volume 2, Issue , Sept. 16 2007-Oct. 19 2007 Page(s):II - 257 - II - 260
[11]  GrabCut,

Suchmaschinen für Literatur:
DBLP Uni Trier
EZB Uni Freiburg
Google Scholar

Albert-Ludwigs-Universität Freiburg, Lehrstuhl für Mustererkennung und Bildverarbeitung, Qing Wang (qwang at
Zuletzt aktualisiert am 27.04.2009, 15:00h