2018-2019 / ELEN0016-2

Computer vision


30h Th, 10h Pr, 50h Proj.

Number of credits

 Master in biomedical engineering (120 ECTS)5 crédits 
 Master in data science (120 ECTS)5 crédits 
 Master in electrical engineering (120 ECTS)5 crédits 
 Master of science in computer science and engineering (120 ECTS)5 crédits 
 Master in data science and engineering (120 ECTS)5 crédits 
 Master in computer science (120 ECTS)5 crédits 


Marc Van Droogenbroeck

Language(s) of instruction

English language

Organisation and examination

Teaching in the first semester, review in January


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

Contents: introduction, linear filtering and deconvolution, mathematical morphology, non-linear filtering, features extraction and border detection, texture, enhancement and restoration, shape analysis, image segmentation, motion detection, aspects of 3D vision, machine learning, pattern recognition, deep learning

Learning outcomes of the learning unit

This course introduces to the major techniques used in computer vision. Theoretical and practical aspects of image processing are discussed in details, with a focus on industrial applications.
At the end of the course, students will be able to:

  • master the notion of an image;
  • understand the major vision processing techniques;
  • design a complete video processing chain with a practical aim.
Exercise sessions, laboratory sessions and a large homework will help the students in developing more general skills like the capacity to evaluate tools, the conception of complete chain from the specifications to the realization, and team working.

Prerequisite knowledge and skills

  • The student shall have passed a course on advanced programming.
  • The student shall be familiar with signal processing concepts.

Planned learning activities and teaching methods

Apart from the theoretical course, there are :

  • exercise sessions
  • computer simulations
  • a large project (which is compulsory) consisting in a software implementation of computer vision techniques applied to a real situation

Mode of delivery (face-to-face ; distance-learning)

It includes a lecture on theory and training session per week. The project must be delivered by the end of the first semester.

Recommended or required readings

Slides : http://orbi.ulg.ac.be/handle/2268/184667

Assessment methods and criteria

Written exam which is compulsory except if the project has been rated with a note larger or equal to 10/20.
Homework (compulsory). This work must imperatively be given during the penultimate week of course of the first semester. Failure to achieve the required activities during the year will result in denying the possibility to pass the exam (1st AND 2d sessions!). There is no possibility to acheive the work during another semester than the one of the course. 
Methods of examination: The exam is composed of theoritical questions and exercises. This is an open-book exam.

Work placement(s)

Organizational remarks

Please note that the course is given in english!


Teacher : M. Van Droogenbroeck (04/366 26 93) Secretary : 04/ 366 26 91 Assistant : P. Latour