摘要
提出了利用二次曲线分段拟合导出的梯度模板对焊缝缺陷进行检测的算法,并按人眼视觉特性对焊缝缺陷进行轮廓跟踪,从而有效地检测出焊缝缺陷。统计识别和模糊识别方法相结合,根据焊缝缺陷的形状特征,对各种焊缝缺陷进行识别分类。按照焊缝质量评级的国家标准对焊缝缺陷进行单独评级及综合评级。试验结果表明,术文提出的方法不但能给出正确的检测与评级结果且有较高的检测速度。
This paper presents a defect detection algorithm to detect the defects of welding image successfully. This algorithm is based on the gradi(?)nt mask which is derived from piecewise fitting method using quadratic function and contour tracing method according to the human vision characteristics. By incorporating statistic recognition with fuzzy recognition and analysing the shapes and features of the welding defects, various welding defects are recognized and classified. Individual and comprehensive quality classifications are made for the welding defects according to the National Standard. The experimental results show that the proposed method performs satisfactorily for the defect detection and quality classification with higher inspection speed.
出处
《焊接学报》
EI
CAS
CSCD
北大核心
1992年第1期1-6,共6页
Transactions of The China Welding Institution
关键词
图象识别
计算机
焊缝
质量检测
image recognition
computer vision
welding quality inspection
defect recognition
quality classification
