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.