Image processing and computer vision
[ELEC2885]
[30h + 30h] 5 credits
This course is taught in the 1st semester.
Teacher(s): Christophe De Vleeschouwer(coord.), Benoît Macq
Language: English
Level: Second
Aims
Main themes
Content and teaching methods
Human perception
2D Discrete Fourier Transform
Linear and non-linear filtering
Orthogonal transforms and sparse approximation
Image and video compression
Morphological image processing
Feature detection (edges, corners, textures)
Segmentation and shape analysis
Multimodal images registration
Detection and recognition of objects
Object tracking in video sequences
Lecture
Paper reviews and discussion
Learning by projects : a number of practical problems will be solved based on conventional image processing software platforms.
Other information (prerequisite, evaluation (assessment methods), course materials recommended readings, ...)
Signal processing, signals and systems, and stochastic processes
Evaluation :
. One final exam : to help you to grasp the fundaments of today's image processing
. One project : it consists in the implementation and the critical analysis of an algorithm proposed in the literature
. Paper reviews : students are expected to read papers before some of the classes, submit a summary for each paper, and participate in the discussion during the class
Support :
Slides, reference papers, and software libraries (Matlab, Open CV)