Extraction of weld defect from radiographic images using the level set segmentation without reinitialization

Auteurs :  RAMOU Naim, HALIMI Mohammed
Année : 2013
Domaine : Electronique
Type : Communication
Conférence: IEEE International Conference on Computer Applications Technology (ICCAT), 2013
Résumé en PDF :  (résumé en pdf)
Fulltext en PDF :  (.pdf)
Mots clés : Image segmentation; active contour; level set

Résumé : 

All level set based image segmentation methods arebased on an assumption that the level set function is close to asigned distance function (SDF). Small time step and costly reinitialization procedure must be applied to guarantee this assumption, and in order to calculate the gradient, simple numerical schemes, based on finite differences, are applied. Inthis paper, in order to achieve higher order accuracy in thetemporal discretization, we have used Total Variation Diminishing (TVD) Runge Kutta (RK) methods. The spatial derivatives are determined by using the Weighted Essentially Non-Oscillatory methods (WENO-5) that accurately capture theformation of sharp gradients in the moving fronts. In the otherhand, we have used the level set method without re-initializationin order to speed up the evolutionary process. Experiments results show that we have obtained good results both on syntheticand real images.