Image processing and computer vision

At the end of this learning unit, the student is able to :

With respect to the AA referring system defined for the Master in Electrical Engineering, the course contributes to the develoopment, mastery and assessment of the following skills :

• AA1.1, AA1.2
• AA3.1, AA3.3
• AA5.5, AA5.6

b.   At the end of this course, the student will be able to:

1. Handle techniques of representation and approximation of images in order to extract their meaningful components with respect to a particular application, for example, in the fields of data transmission or interpretation;
2. Apply linear and non-linear filtering operations (e.g., morphological) to isolate certain frequency components or to cancel particular noises;
3. Detect structures of interest in an image, such as contours, key features, etc..
4. Segment an image into regions of homogeneous characteristics, targeting a semantic interpretation of the image content;
5. Restore images corrupted a noise or a blurring;
6. Understand the basic principles of inverse problem solving in imaging and in compressed sensing;
7. Manage image databases using detection tools or classification;
8. Detect and track one or more object(s) of interest in video streams, in biomedical applications or for 3-D scene interpretation;
9. Compress image signals considering their visual perception and their accessability in the compressed signal representation;
10. Provide a solution to complex problems involving image processing, such as quality control, visiosurveillance, multimodal human-machine interfaces, and image compression.