1. Accueil
  2. EN
  3. Studying at ULB
  4. Find your course

Image acquisition and processing

academic year

Course teacher(s)

Olivier DEBEIR (Coordinator)

ECTS credits


Language(s) of instruction


Course content

  • Introduction: examples of application of the image processing from several domains, medical applications, industry, HCI...
  • Human vision fundamentals 
  • Acquisition
  • Definitions : the image processing chain
  • Quantification : spatial, spectral and intensity color representation different acquisition modalities sensor,sensor+source,...
  • Acquisition devices : CCD, CMOS, vidicon ultrasound light time-of-flight (TOF)
  • Notions of compression : run-length-coding, hierarchical decomposition, Jpeg lossy compression
  • Pre-processing - Histogram based image enhancement
  • Linear filtering Fourier transform
  • Fourier domain processing : e.g. interlaced image correction pattern matching
  • Image restoration : Wiener filtering rank filter
  • Morphomatematics definitions : ensemble, structuring element
  • Basic operators : erosion, dilation, duality combined operators : opening, closing
  • Hit-or-miss operator thinning and opening : skeleton, pruning,...
  • Gray-level morphology watershed transform
  • Segmentation/ object detection pixel based : threshold : optimal, Otsu
  • Color segmentation border based: gradient, Laplacian, LoG
  • Region based : split and merge, watershed(recall) mean-shift
  • Hough transform
  • Object description binary, image labelling, chain code, polygonal approximation, Fourier descriptors, invariant moments, convexity, fractal dimension, texture

Objectives (and/or specific learning outcomes)

Become familiar with basic numerical image processing

  • be able to recognize image properties
  • to apply basic filtering and denoising
  • to segment an image using classical methods
  • theoretical and practical skills are expected.


Courses requiring this course

Teaching methods and learning activities

Ex cathedra + practical work

Contribution to the teaching profile

This teaching unit contributes to the following competences:

  • Traiter et analyser des signaux de toute nature, 1D, image, vidéo, en particulier ceux issus des dispositifs médicaux

  • Se représenter les mécanismes biologiques fondamentaux depuis la biochimie de la cellule jusqu’au fonctionnement des principaux systèmes de la physiologie humaine

  • Gérer, explorer et analyser les données médicales (dossier médical, imagerie, génomique, statistiques)

  • Communiquer en anglais dans le domaine de l’ingénierie

References, bibliography, and recommended reading

  • Handbook of Image & Video Processing
  • Alan C. Bovik (Editor)
  • Digital Image Processing: Concepts, Algorithms, and Scientific Applications
  • Bernd Jahne (Author)
  • Digital Image Processing
  • Rafael C. Gonzalez (Author), Richard E. Woods (Author)
  • Image Processing, Analysis, and Machine Vision
  • Milan Sonka (Author), Vaclav Hlavac (Author), Roger Boyle (Author)
  • A Wavelet Tour of Signal Processing, Second Edition (Wavelet Analysis & Its Applications).. Stephane Mallat (Author)
  • The Image Processing Handbook, Second Edition
  • John C. Russ (Author)
  • Handbook of Medical Imaging: Processing and Analysis Management (Biomedical Engineering)
  • Isaac Bankman (Editor)
  • Handbook of Medical Imaging, Volume 2. Medical Image Processing and Analysis
  • J.Michael Fitzpatrick (Author), Milan Sonka (Author)
  • Active Contours: The Application of Techniques from Graphics, Vision, Control Theory and Statistics to Visual Tracking of Shapes in Motion
  • Andrew Blake (Author), Michael Isard (Author)
  • Handbook of Computer Vision and Applications, Three-Volume Set
  • Bernd Jahne (Editor), Horst Haussecker (Editor), Peter Geissler (Editor)
  • Mathematical Methods and Algorithms for Signal Processing
  • Todd K. Moon (Author), Wynn C. Stirling (Author)
  • Pattern Recognition Engineering
  • Morton Nadler (Author), Eric P. Smith (Author)
  • Mathematical Morphology in Image Processing (Optical Science and Engineering) [Hardcover]
  • Edward Dougherty (Author)
  • Digital Image Processing Methods (Optical Science and Engineering)
  • Dougherty (Author)

Course notes

  • Podcast
  • Université virtuelle

Other information






Method(s) of evaluation

  • Other

  • The evaluation of the practical work will be done on the basis of a series of assignments to be handed in during the term.
  • Oral exam without note, depending on the circumstances, exam can be done remotely using Teams.

Mark calculation method (including weighting of intermediary marks)

80% oral exam + 20% on the quality of Practice work
oral exam (2 questions without notes)

  • 1 theory question 50%
  • 1 problem based question 50%

Language(s) of evaluation

  • english
  • (if applicable french )