Segmentation of the Weld Radiographic Images by the Level Set Method using the Kernel Fuzzy C-Means Clustering.

Type : Article de conférence
Auteur(s) :  N. Chetih, N. Ramou, Y. Boutiche, M. SAHNOUN
Année :  2016
Domaine : Electronique
Conférence: International Conference on Recent Advances in Electrical Systems (ICRAES’2016).
Résumé en PDF :  (résumé en pdf)
Fulltext en PDF :  (.pdf)
Mots clés :  Level set, kernel fuzzy c-means, weld defects, weld radiographic images, image segmentation

Résumé : 

In this paper, we are interested to segment weld radiographic images using the level set method (LSM) based on kernel fuzzy c-means clustering (KFCM) in order to extract the region of interest (weld defects) and to improve the precision of segmentation. The proposed approach contains two successive necessary stages. The first one consists in the application of kernel fuzzy c-means algorithm to get a clustered image. The second stage is based on the using of the appropriate class of the clustered image as an initial contour of the level set method to extract the defects boundaries. The experimental results have shown that the proposed model can extract successfully the interest region from image and confirm its efficiency for welding defects segmentation.