Bayesian Networks-Based Defects Classes Discrimination in Weld Radiographic Images

International audienceBayesian (also called Belief) Networks (BN) is a powerful knowledge representation and reasoning mechanism. Based onprobability theory involving a graphical structure and random variables, BN is widely used for classification tasks and in thispaper, BN is used as a class discrimination tool for a set of weld defects radiographic images using suitable attributes based oninvariant geometric descriptors. Tests are performed on a database of few hundred elements where the results are outstanding and verypromising, since they outperform those given by powerful SVM classifiers