Special Topics in Computer Science:

Random Fields and Active Contours in Image Segmentation

339.012 1KV Kato Block Begin: 28.4.2009

There are two main approaches to image segmentation: Contour-based methods aim at detecting the boundary between regions, while region-based methods try to identify the regions directly. In this course we will address modern techniques of both approaches.
1) Active contours are energy-minimizing splines used to locate region boundaries.
2) Markov Random Fields are often used to capture contextual constraints in a probabilistic framework, allowing for efficient region-based segmentation of complex images.


Dr. Zoltan Kato
University of Szeged
Institute of Informatics
Department of Image Processing and Computer Graphics


Date Time Room
Tu 28.4.2009 15:30 - 18:45 KG 712
We 29.4.2009 15:30 - 18:00 T 041
Th 30.4.2009 15:30 - 18:00 UC 5


Part I: Variational methods

  1. Mumford-Shah energy functional
  2. Classical Active contour (Snake)
  3. Region-based Active contours

Part II: Markov Random Fields

  1. Segmentation model
  2. Energy minimization
  3. Parameter estimation via the EM algorithm


Students will have to do a project and send it to the lecturer. The marks for this course will be based on the project.


Some brief lecture notes are available for part I:

For part II the following PhD thesis covers most of the material presented: