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Publications sur Modele de Ginzburg-Landau
Résultat de la recherche dans la liste des publications :
Article |
1 - Detecting codimension-two objects in an image with Ginzburg-Landau models.
G. Aubert et J.F. Aujol et L. Blanc-Féraud. International Journal of Computer Vision, 65(1-2): pages 29-42, novembre 2005.
Mots-clés : Modele de Ginzburg-Landau, Detection de points, Segmentation, PDE, Images biologiques, Images SAR.
@ARTICLE{laure-ijcv05,
|
| author |
= |
{Aubert, G. and Aujol, J.F. and Blanc-Féraud, L.}, |
| title |
= |
{Detecting codimension-two objects in an image with Ginzburg-Landau models}, |
| year |
= |
{2005}, |
| month |
= |
{novembre}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{65}, |
| number |
= |
{1-2}, |
| pages |
= |
{29-42}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/GL_IJCV_5.pdf}, |
| keyword |
= |
{Modele de Ginzburg-Landau, Detection de points, Segmentation, PDE, Images biologiques, Images SAR} |
| } |
Abstract :
In this paper, we propose a new mathematical model for detecting in an image singularities of codimension greater than or equal to two. This means we want to detect points in a 2-D image or points and curves in a 3-D image. We drew one's inspiration from
Ginzburg-Landau (G-L) models which have proved their efficiency for modeling many phenomena in physics. We introduce the model, state its
mathematical properties and give some experimental results demonstrating its capability in image processing. |
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Rapport de recherche et Rapport technique |
1 - Detecting Codimension-two Objects in an Image with Ginzburg-Landau Models.
G. Aubert et J.F. Aujol et L. Blanc-Féraud. Rapport de Recherche 5254, INRIA, France, juillet 2004.
Mots-clés : Modele de Ginzburg-Landau, Images biologiques, Segmentation, Equation aux derivees partielles.
@TECHREPORT{5254,
|
| author |
= |
{Aubert, G. and Aujol, J.F. and Blanc-Féraud, L.}, |
| title |
= |
{Detecting Codimension-two Objects in an Image with Ginzburg-Landau Models}, |
| year |
= |
{2004}, |
| month |
= |
{juillet}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{5254}, |
| address |
= |
{France}, |
| url |
= |
{https://hal.inria.fr/inria-00070744}, |
| pdf |
= |
{https://hal.inria.fr/file/index/docid/70744/filename/RR-5254.pdf}, |
| ps |
= |
{https://hal.inria.fr/docs/00/07/07/44/PS/RR-5254.ps}, |
| keyword |
= |
{Modele de Ginzburg-Landau, Images biologiques, Segmentation, Equation aux derivees partielles} |
| } |
Résumé :
Dans cet article, nous proposons a nouveau modèle mathématique pour détecter dans une image les singularités de codimension supérieure ou égale à deux. Cela signifie que nous voulons détecter des points dans des images 2-D, ou des points et des courbes dans des images 3-D. Nous nous inspirons des modèles de Ginzburg-Landau (GL). Ces derniers se sont révélés efficace pour modéliser de nombreux phénomènes physiques. Nous introduisons le modèle, nous énonçons ses propriétés mathématiques, et nous donnons des résultats expérimentaux illustrant les performances du modèle. |
Abstract :
In this paper, we propose a new mathematical model for detecting in an image singularities of codimension greater than or equal to two. This means we want to detect points in a 2-D image or points and curves in a 3-D image. We drew one's inspiration from Ginzburg-Landau (G-L) models which have proved their efficiency for modeling many phenomena in physics. We introduce the model, state its mathematical properties and give some experimental results demonstrating its capability. |
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