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Published in:
2009 | OriginalPaper | Chapter
Bayesian Pressure Snake for Weld Defect Detection
Authors : Aicha Baya Goumeidane, Mohammed Khamadja, Nafaa Naceredine
Published in: Advanced Concepts for Intelligent Vision Systems
Publisher: Springer Berlin Heidelberg
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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.