Coursebooks 2017-2018

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Image analysis and pattern recognition

EE-451

Lecturer(s) :

Thiran Jean-Philippe

Language:

English

Summary

This course gives an introduction to the main methods of image analysis and pattern recognition.

Content

Introduction
Digital image acquisition and properties.
Pre-processing: geometric transforms, linear filtering, image restoration.
Introduction to Mathematical Morphology
Examples and applications

Segmentation and object extraction
Thresholding, edge detection, region detection.
Segmentation by active contours. Applications in medical image segmentation.

Shape representation and description
Contour-based representation, region-based representation. Morphological skeletons

Shape recognition
Statistical shape recognition, Bayesian classification, linear and non-linear classifiers, perceptrons, neural networks and unsupervised classifiers.
Applications.

Practical works on computers

Learning Prerequisites

Recommended courses

Introduction to signal processing, Image processing

Learning Outcomes

By the end of the course, the student must be able to:

Transversal skills

Teaching methods

Ex cathedra and practical work and oral presentation by the students

Assessment methods

Continuous control

Resources

Ressources en bibliothèque

Prerequisite for

Semester project, Master project, doctoral thesis

In the programs

  • Bioengineering, 2017-2018, Master semester 2
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Image analysis and pattern recognition
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Practical work
      2 Hour(s) per week x 14 weeks
  • Bioengineering, 2017-2018, Master semester 4
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Image analysis and pattern recognition
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Practical work
      2 Hour(s) per week x 14 weeks
  • Data Science, 2017-2018, Master semester 2
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Image analysis and pattern recognition
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Practical work
      2 Hour(s) per week x 14 weeks
  • Electrical and Electronics Engineering, 2017-2018, Master semester 2
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Image analysis and pattern recognition
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Practical work
      2 Hour(s) per week x 14 weeks
    • Practical work
      2 Hour(s) per week x 14 weeks
  • Electrical and Electronics Engineering, 2017-2018, Master semester 4
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Image analysis and pattern recognition
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Practical work
      2 Hour(s) per week x 14 weeks
    • Practical work
      2 Hour(s) per week x 14 weeks

Reference week

MoTuWeThFr
8-9
9-10
10-11
11-12
12-13
13-14
14-15
15-16
16-17
17-18
18-19
19-20
20-21
21-22
Under construction
Lecture
Exercise, TP
Project, other

legend

  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German