Abstract
Image Segmentation plays a key role in automatic weld defect detection and classification in radiographic testing. Among the segmentation methods, boundary extraction based on deformable models is a powerful technique to describe the shape and then deduce after the analysis stage, the type of the defect under investigation. This paper describes a method for automatic estimation of the contours of weld defect in radiographic images. The method uses a statistical formulation of contour estimation by exploiting statistical pressure snake based on non-parametric modeling of the image. Here the edge energy is replaced by a region energy which is a function of statistical characteristics of area of interest.
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Goumeidane, A.B., Khamadja, M., Naceredine, N. (2009). Bayesian Pressure Snake for Weld Defect Detection. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04697-1_29
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DOI: https://doi.org/10.1007/978-3-642-04697-1_29
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