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

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 )