Skip to Main content Skip to Navigation
Theses

Ondelettes pour la détection de caractéristiques en traitement d'images. Application à la détection de région d'intérêt.

Abstract : This thesis in image processing addresses the problem of the highlight of some remarquable structures, such as objects we perceive visually. These can be monodimensional, like contours, as well as bidimensional, corresponding to more complex objects. An important problem in computer vision consists on detecting such structures, and also extracting characteristic features from them. In many applications, such as object recognition, image matching, motion tracking or the enhancement of some particular elements, it is a first step before other high-level operations. Thereby, the formulation of performant detectors appears as essential. We show that this can be carried out using wavelet decompositions; in particular, it is possible to define some maxima lines, which turn out as relevant to this problem : one the one hand, so as to detect objects (given by some regions of interest), and, on the other hand, in order to characterize them (computations of Lipschitz regularity and of characteristic scale). This original approach for detection, based on maxima lines, can thus be compared to classical approches.
Document type :
Theses
Complete list of metadatas

Cited literature [129 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-00287008
Contributor : Christophe Damerval <>
Submitted on : Tuesday, June 10, 2008 - 3:23:36 PM
Last modification on : Thursday, November 19, 2020 - 1:00:55 PM
Long-term archiving on: : Friday, September 28, 2012 - 3:50:12 PM

Identifiers

  • HAL Id : tel-00287008, version 1

Collections

Citation

Christophe Damerval. Ondelettes pour la détection de caractéristiques en traitement d'images. Application à la détection de région d'intérêt.. Mathématiques [math]. Université Joseph-Fourier - Grenoble I, 2008. Français. ⟨tel-00287008⟩

Share

Metrics

Record views

554

Files downloads

19500