Coursebooks

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

Transversal skills

Teaching methods

Ex cathedra and practical work and oral presentation by the students

 

Assessment methods

Continuous control

Resources

Bibliography

Reconnaissance des formes et analyse de scènes / Kunt

Image processing, Analysis and Machine Vision / Sonka

Ressources en bibliothèque

Prerequisite for

Semester project, Master project, doctoral thesis

In the programs

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

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