In recent years, graphs have emerged as a unified representation for image analysis and processing. Many powerful image processing methods have been formulated on pixel adjacency graphs, i.e., a graph whose vertex set is the set of image elements (pixels), and whose edge set is determined by an adjacency relation among the image elements. Due to its discrete nature and mathematical simplicity, this graph based image representation lends itself well to the development of efficient, and provably correct, methods for image processing. In this course, we will give an overview of recent developments in this field. Topics covered include graph-based methods for:
- Classification and clustering
- PhD Filip Malmberg, Centre for Image Analysis, Uppsala university. (webpage)
- Prof. Alexandre Falcão, Institute of Computing, State University of Campinas, Brazil. (webpage)
- MSc Erik Wernersson, Centre for Image Analysis, Swedish University of Agricultural Sciences. (webpage)
Sign up for the course by emailing Filip Malmberg. Deadline for registration is one week before the course start.
Each participant should also select a topic for her individual project. The project can be applied or theoretical. The results of the project work should be presented in a written report in order to achieve full credits for the course.
Student who complete the assignment get 5 hp. The examiner is Filip Malmberg