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INFO-H500
Image acquisition and processing
Branch(es) of study : Engineering sciences
Course teacher(s)
Olivier DEBEIR (Coordinator)ECTS credits
5
Language(s) of instruction
english
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.
Prerequisites and Corequisites
Cours ayant celui-ci comme co-requis
Teaching methods and learning activities
Ex cathedra + practical work
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
Contribution to the teaching profile
This teaching unit contributes to the following competences:
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Traiter et analyser des signaux de toute nature, 1D, image, vidéo, en particulier ceux issus des dispositifs médicaux
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Se représenter les mécanismes biologiques fondamentaux depuis la biochimie de la cellule jusqu’au fonctionnement des principaux systèmes de la physiologie humaine
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Gérer, explorer et analyser les données médicales (dossier médical, imagerie, génomique, statistiques)
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Communiquer en anglais dans le domaine de l’ingénierie
Other information
Contacts
odebeir@ulb.ac.be
Campus
Solbosch
Evaluation
Method(s) of evaluation
- Oral examination
- Written report
Oral examination
Written report
- 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.
In order to certify your regular and personal work, you are requested to use a version control tool such as GIT (preferably https://gitlab.ulb.be/) to record the progress of your practical work.
We ask that you DO NOT use generative AI to complete your practical work. This is considered bad practice and goes against the objective of learning by doing. In all cases, you will be assessed on your understanding of the code you submit.
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 )