Classification of welding defects in radiographic images

Welding defects detection and classification is very important to guarantee the welding quality. Over the last 30 years, there has been a large amount of research attempting to develop an automatic (or semiautomatic) system for the detection and classification of weld defects in continuous welds using radiography. In this paper, we describe an automatic system for classification of welding defects from radiographic images and compare with KNN and SVM classifiers. We classify and recognize the linear defects such as lack of penetrations, incomplete fusion and external undercut. Experimental results have shown the classification method is useful for the lengthy defects and obtained through our method is better than the two classifiers methods.