现代制造工程Issue(10)：106-109,4.DOI:10.16731/j.cnki.1671-3133.2017.10.020
基于支持向量机的焊缝缺陷类型识别研究
Type recognition of weld defects based on support vector machines
摘要
Abstract
For linear and circular two kinds of weld defects ,proposed a method of weld defect type recognition algorithms based on Support Vector Machine (SVM).First of all,some image pre-processing algorithms such as fuzzy C means clustering ,region fill-ing algorithm,average filtering,edge detection,Otsu thresholding and inverse thresholding ,to get the approximate location of weld defects .The information of the particular region will be extracted using segmentation based fractal texture analysis ,SVM is used to classify the segmented defect as line or circular defects based on the extracted features lastly .The results showed that ,the average accuracy rate is 97.5%for correcting identification of the type of weld defects ,by 150 weld X-ray image is trained and 80 X-ray image weld test ,which can meet industrial requirements .关键词
焊缝/缺陷/图像处理/支持向量机Key words
weld/defect/image processing/Support Vector Machine ( SVM)分类
信息技术与安全科学引用本文复制引用
李宁,卢子广..基于支持向量机的焊缝缺陷类型识别研究[J].现代制造工程,2017,(10):106-109,4.基金项目
广西高等学校优秀中青年骨干教师培养工程资助项目 （）
