基于列处理的T型焊件微焦点X射线检测图像缺陷分割

Defects Segmentation of Micro-focus X-ray Detection Image of T-shaped Weldments Based on Column Pixel Processing

为实现T型焊件缺陷的空间定位和可视化,须对X射线检测图像进行准确的缺陷分割。在分析T型焊件微焦点X射线检测图像行列线灰度分布曲线特点的基础上,利用基于列处理的背景模拟方法,通过单列滑动模板逐次处理图像的列像素,平滑、滤除缺陷和噪声,成功实现了检测图像的背景模拟。而后结合阈值分割等完成了焊接缺陷的保真分割,并与形态学、均值滤波两种背景模拟方法的缺陷分割结果进行了对比。试验结果表明,采用提出的算法可对检测图像中的焊缝缺陷进行有效的分割,避免了其它背景模拟方法造成的漏检和过分割,为后续的缺陷细化和缺陷空间位置数据的自动提取奠定了良好基础。

In order to achieve the location and visualization of defects in T-shaped weldments, defect segmentation of X-ray detection image must be done accurately. Based on the analysis of the grey distribution curve of micro-focus X-ray detection images of T-shaped weldment in horizontal and vertical directions, the column pixels of image were processed by single column sliding template step by step, defects and noise were smoothed and filtered, the background simulation of the detected images was achieved successfully. Combining with the method of threshold segmentation, the segmentation of weld defects were completed accurately, and the results were compared with those of the two background simulation methods of morphology and mean filter. The experimental results show that the weld defects in the detection images are segmented effectively by the proposed algorithm, and it can avoid the problem such as missed detection, over segmentation and so on caused by other simulation methods. At the same time, it can provide good basis for subsequent defects thinning and automated extraction of spatial position data.