MU4IN600 BIMA: year 2020-2021

Table des matières

Informations

BIMA (MU4II600) is a compulsory course for IMA (M1) and VCC (Entry) hosted in the Master of Computer Science from Sorbonne University. It provides fundamentals knowledge on Image processing and Computer vision.

  • Beginning of lectures: week of 28 September 2020
  • Beginning of tutorial and practical works: week of 5 October 2020
  • Final written exam: somewhere in January
  • Final written exam (second chance): in June

Teachers:

Schedule and classroom

Please, check each week in the official schedule of the master the location of classrooms: https://cal.ufr-info-p6.jussieu.fr/master/

  • Group 1 (French spoken):
    • lecture: on Tuesday, 13h45-15h45
    • tutorial works: on Thursday, 13h45-15h45
    • practical works: on Thursday, 16h00-18h00
  • Group 2 (English spoken):
    • lecture: on Monday, 8h30-10h30
    • tutorial works: on Tuesday, 8h30-10h30
    • practical works: on Tuesday, 10h45-12h45

Evaluation

  • Final written exam
  • Evaluation of pratical works

First part: basics

  • Practical works are done with Jupyter notebook and Python/Numpy, see Jupyter notebook section.
  • Practical works are to be submitted on our Moodle web site
  • Book of exercises (tutorial and pratical works), part 1
  • Links of a given week are only active as from the week before the lecture

Jupyter notebook

  • On your own computer (all operating system):
    • installation:
      1. Install anaconda ou miniconda (miniconda is recommended)
      2. In a text terminal Linux, OSX, or Windows, type:

        % conda create -n bima python=3
        % conda activate bima
        % conda install numpy Pillow matplotlib scipy 
        % conda install jupyter	
        
    • usage: open a text terminal and type:

      % conda activate bima
      % jupyter-notebook TME1.ipynb
      
  • at the University (see PPTI web site), open a text terminal and type:

    % jupyter-notebook TME1.ipynb
    

Week 1: Introduction

  • No tutorial and practical works this week
  • Lecture

Week 2: Image enhancement

Week 3: Fourier transform

Week 4: Digitization of images, advanced Fourier transform

Week 5: Image filtering, colors

Week 6: Edges detection

Second part: applications

  • Book of exercises (tutorial and pratical works), part 2

Week 7: Extraction of image primitives

Week 8: Segmentation

Week 9: Image descriptors - similarity

Week 10: Pattern recognition, PCA, Eigenfaces

Week 11: PCA, Eigenfaces

  • No lecture this week

Annals (in french)

Bibliography (books)

Created: 2020-09-08 Mar 13:12

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