Research on SVM Based Classification for Welding Defects in Radiographic Testing

After analysis of the welding defect features, five typical features are successfully extracted from the welding defect features. Binary decision tree is used to make a greatest distinction between welding defects. Therefore, a support vector machines based binary decision tree is proposed, which owns good performance in the classification and the noticeable achievements are made in the classification of welding defects with the proposed method.