DR图像中气孔缺陷的自动检测与识别

Automatic Detection and Recognition of Gas Pores in DR Images

焊接缺陷的自动检测与识别是无损检测领域的研究热点之一。首先构造了一个平滑模板,对原始图像进行中值滤波,得到理想焊缝图像。其次进行图像减影操作,当灰度连通性超过给定的阈值T时,当前位置被标志为可疑缺陷,从而实现焊缝图像中可疑缺陷的自动检测;自动检测后得到4个可疑缺陷,计算所有可疑缺陷的特征参数,定性分析后均判定为气孔;最后得到了缺陷列表,缺陷列表与气孔缺陷二值图像之间建立了一一对应关系。

Automatic detection and recognition of weld defects is one of the hot spots in nondestructive testing. In this paper, firstly, a smooth template was constructed, the original image was filtered by median filter, and then the ideal weld image was constructed. Secondly, the image subtraction operation was performed, and the current position was marked as a suspicious defect when the gray connectivity exceeded a given threshold value of T, then automatic detection of weld defects was realized. Four suspicious defects were obtained after automatic detection, the characteristic parameters of all suspicious defects were calculated, and all suspicious defects were determined as gas pores after qualitative analysis. Finally, the defect list was obtained, and the correspondence between the defect list and the two value image of gas pores was established.