低密度粉末材料的DR图像夹杂检测

Inclusion Detection from DR Images of Low-Density Powder Materials

针对单次扫描角度不同引起的夹杂检测误差较大、稳定性低等问题,提出了一种低密度粉末材料的多角度数字化X射线摄影(DR)扫描夹杂检测方法。首先对被测对象进行多角度DR检测;然后采用尺度不变特征变换(SIFT)特征匹配的方法寻找不同角度下夹杂的图像,自动选取不同角度下夹杂尺寸的最大值作为近似值;最后建立不同角度下夹杂面积和旋转角度的关系,并预测出夹杂的最大面积和旋转角度。实验结果表明,所提方法解决了计算机断层扫描(CT)效率低的问题,相比单次扫描检测方法,进一步提高了检测的准确性和稳定性,并且较小旋转角度下的预测具有较高置信度,能够满足实际生产检测需求。

In this study,we propose a method for multi-angle digital radiography(DR)scanning inclusion detection of low-density powder materials considering the problems such as large inclusion detection errors and low stability caused by the usage of different single scanning angles.First,multi-angle DR detection is performed with respect to the measured object.Then,the scale-invariant feature transform(SIFT)feature matching method is used to find the inclusion images at different angles.Further,the maximum size of the inclusions at different angles is automatically selected as approximate value.Finally,a relation between the inclusion area and rotation angle is established under different angles and the maximum inclusion area and rotation angle are predicted.The experimental results prove that the proposed method can solve the problem of low efficiency associated with computed tomography(CT)and can improve the accuracy and stability of detection when compared with the single-scan detection method.A high degree of confidence is associated with the prediction at a small rotation angle,which indicates that the proposed method can meet the demands of inclusion detection in practical applications.