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Course unit

Tutorials of image processing

Last updated: 03/04/2024

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Course Director(s):

GAVET Yann

General Description:

The aim of the unit is to provide the fundamental bases of the image processing chain (acquisition, processing, analysis, measuring, decision).

The unit consists of 18 hours of practical course work (using Matlab)

There will be an exam of 1h30 (on computer, using Matlab) to assess the learning from the unit.

Key words:

Image enhancement Human vision Fourier analysis Image filtering Image restauration Image enhancement Image registration Image segmentation Description Characterization

Number of teaching hours

18

Fields of study

Mathematics

Teaching language

French English

Intended learning outcomes

On completion of the unit, the student will be capable of: Classification level Priority
Proposing simple algorithms for image processing null null
Carrying out an image processing operation with a language such as Matlab

Learning assessment methods

Percentage ratio of individual assessment Percentage ratio of group assessment
Written exam: % Project submission: %
Individual oral exam: % Group presentation: %
Individual presentation: % Group practical exercise: %
Individual practical exercise: 66 % Group report: 33 %
Individual report: %
Other(s): %

Programme and content

Type of teaching activity Content, sequencing and organisation
Practical courses

12 practical courses (using Matlab) of 1h30 / 18h :

  • Introduction
  • 2D Fourier transform
  • Filtering by convolution
  • Denoising
  • Deblurring
  • Image enhancement
  • Histogram-based image segmentation
  • Region growing segmentation
  • Complete segmentation application
  • Image characterization