• Aucun résultat trouvé

Weld defect detection with parametric deformable model

N/A
N/A
Protected

Academic year: 2021

Partager "Weld defect detection with parametric deformable model"

Copied!
1
0
0

Texte intégral

(1)

the International Conference on Modeling and Simulation 2007

Weld defect detection with parametric deformable model

A. B. Goumeidane, N. Nacereddine, F. Mekhalfa, M. Khamadja

Abstract : Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to boundary concavities have aroused, which restricts their utility. This paper presents a new approach to deal with the defects contour estimation problem in radiographic images using parametric active contours. In this approach we exploit the performance of the Gradient Vector Flow (GVF) as external force and enhance it by adding external adaptive pressure forces (APF) which speeds up the snake progression, makes it less sensitive to initialization and provides capability of tracking the concavities.

Keywords : : Radiographic testing, Active contour, GVF.

Centre de Recherche en Technologies Industrielles - CRTI - www.crti.dz

Powered by TCPDF (www.tcpdf.org)

Références

Documents relatifs

In this approach we exploit the performance of the GVF as external force and enhance it by joining to it external adaptive pressure forces which bring speed to the snake evolution

In this approach we exploit the performance of the GVF as external force and enhance it by joining to it external adaptive pressure forces which bring speed

In this approach we exploit the performance of the GVF as external force and enhance it by joining to it an external adaptive pressure forces which speeds up to the snake

In this approach we exploit the performance of the GVF as external force and enhance it by joining to it an external adaptive pressure forces which speeds up to the snake

Implementation is performed by a deterministic iterative algorithm that drives the model quickly to the boundaries, by limiting the investigation to the pixels laying in the

Implementation is performed by a deterministic iterative algorithm that drives the model quickly to the boundaries, by limiting the investigation to the pixels

In this approach we exploit the performance of the Gradient Vector Flow (GVF) as external force and enhance it by adding external adaptive pressure forces (APF) which speeds

Implementation is performed by a deterministic iterative algorithm that drives the model quickly to the boundaries, by limiting the investigation to the pixels