Chercheur

Teachers Login Form

 

Admin

Pupils Login Form

 



Radiographic Image Segmentation Based on Gaussian Mixture Model

Auteurs : F. Mekhalfa, N. Nacereddine, A. B. Goumeïdane
Année : 2007
Domaine : Electronique
Type : Communication
Conférence: The Eighth International Symposium On Programming and Systems (ISPS)
Résumé en PDF : (résumé en pdf)
Fulltext en PDF : (.pdf)
Mots clés : — expectation maximization algorithm, fuzzy C-means algorithm, Gaussian mixture model, image segmentation, radiographic images, weld defect

Résumé :

In this work, we propose to use an image segmentation method based on Gaussian mixture model. The observed image is considered as a mixture of multivariate densities and the mixture parameters are estimated by the expectation maximization (EM) algorithm. The segmentation is completed by clustering each pixel into a component according to the maximum likelihood (ML) estimation. This method has been applied to a variety of radiographic images of weld defects and satisfactory segmentation results have been reported.