3D Reconstruction of Volume Defects from Few X-Ray Images

Abstract

In nondestructive testing for quality control of industrial objects the standard X-ray analysis produces a 2D projection of the 3D objects. Defects can be detected but cannot be localized in 3D position, size and shape. Tomographic testing equipment turns frequently out to be too costly and time consuming for many applications. Here a new approach for 3D reconstruction is suggested using standard X-ray equipment without costly positioning equipment. The new approach requires only a small number of X-ray views from different directions in order to reduce the image acquisition time.

The geometric and photometric imaging properties of the system are calibrated using different calibration patterns. The parameters of a CAHV camera model are obtained for each view permitting the exact registration of the acquired images. The efficiency of the 3D reconstruction algorithm has been increased by limiting the reconstruction to regions of interest around the defects. This requires an automated segmentation. The 3D reconstruction of the defects is performed with an iterative procedure. Regularization of the reconstruction problem is achieved on the basis of the maximum entropy principle. The reliability and robustness of the method has been tested on simulated and real data.