Probabilistic deformable models for weld defact contour estimation in radiography

Authors:
N. Nacereddine;L. Hamami;D. Ziou;M. Tridi
Affiliations:
Sign. and Imag. Proc. Laboratory, Research Center in Welding and NDT, Algiers, Algeria;Department of Electronics, Polytechnic National School, Algiers, Algeria;Department of Mathematics and Computer Science, Sherbrooke University, Sherbrooke, Canada;Sign. and Imag. Proc. Laboratory, Research Center in Welding and NDT, Algiers, Algeria
Venue:
Machine Graphics & Vision International Journal
Year:
2006

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Abstract

This paper describes a novel method for segmentation of weld defect in radiographic images. Contour estimation is formulated as a statistical estimation problem, where both the contour and the observation model parameters are unknown. Our approach can be described as a region-based maximum likelihood formulation of parametric deformable contours. This formulation provides robustness against the poor image quality, and allows simultaneous estimation of the contour parameters together with other parameters of the model. Implementation is performed by a deterministic iterative algorithm with minimal user intervention. Results testify very good performance of such contour estimation approach.