Weld Defect Detection of X-ray Images Based on Support Vector Machine

Support vector machines (SVM) have received widespread attention for their excellent ability to learn, and have been applied in many fields. The application of SVM in weld defect defection of X-ray images is receiving more and more attention, which has led to the rapid development of weld defect detection automation. In this paper, a method of weld defect detection based on SVM is proposed. First, all potential defects are detected by a novel method based on grey-level profile analysis. Then three feature vectors are extracted from potential weld defects and used to train the SVM. Lastly, the trained SVM is used to distinguish real defects from potential defects. Results show that the proposed method can achieve a high correct defection rate.