Number of hours
- Lectures 6.0
- Projects 0
- Tutorials 6.0
- Internship 0
- Laboratory works 8.0
ECTS
ECTS 2.0
Goal(s)
This course present some advanced tools for image analysis.
The first part of the course is devoted to review some advanced linear and non linear filtering techniques.
The second part deals with image segmentation (i.e., the partitioning of an image into regions), description of the image regions and classification.
The course ends giving some outlines on video processing and analysis of 3D images.
The lab sessions (BE) associated to this course will allow the students to do some practice on the use of some of the techniques presented during the course. Students will work in groups of two and are requested to submit a report detailing their work.
The cours will be taught in English. However, if needed interactions can be done also in French.
The assignments of the lab sessions will be in English, the reports can be either done in English or French.
Content(s)
Outline of the course
1) Introduction to the course and image color spaces
2) Mathematical morphology (advanced operators)
3) Advanced filtering
4) Edge detection
5) Segmentation part I
6) Segmentation part II
7) Region descriptors and classification
8) Basics on video processing and 3D image analysis
Prerequisites
Basic concepts of image processing (such as histogram, linear filtering, basic mathematical morphology, edge detection etc).
Test
The evaluation is based on both a written examination and on the reports of the lab sessions.
The text of the written exam will be both in English and French. Answers can be done either in English or French.
Final grade = 0.6 x mark of the written exam + 0.4 x average of the marks given to the reports of the lab sessions
Note finale = 0,6 x note d'examen écrit + 0,4 x moyenne des notes de rapports de TP
Final grade = 0.6 x mark of the written exam + 0.4 x average of the marks given to the reports of the lab sessions
Additional Information
Course list
Curriculum->Master->Semester 9
Curriculum->Double-Diploma Engineer/Master->Semester 9
Bibliography
Main references of the course.
Gonzalez, Rafael C., and Richard E. Woods. "Digital image processing." (2002).
Szeliski, Richard. Computer vision: algorithms and applications. Springer, 2010. (available at http://szeliski.org/Book/)
Some of the concepts presented at the course can be found in the following references.
Soille, Pierre. Morphological image analysis: principles and applications. Springer-Verlag New York, Inc., 2003.
Sapiro, Guillermo. Geometric partial differential equations and image analysis. Cambridge university press, 2006.
Gonzalez, Rafael C., Richard Eugene Woods, and Steven L. Eddins. Digital image processing using MATLAB. 2004.