High-precision alignment of X-ray CT volume and CAD data of products based on geometric features

Abstract

X-ray CT scanning is effective to inspect the geometry and positional relationship of parts in assembled objects. For further application of CT data, for example for measurement or design, parts segmentation and extraction is necessary. However, it is still difficult to correctly separate two parts sharing a narrow gap on the CT data. This issue can be reduced by a use of the design data (CAD mesh) of the object. In order to automatically recognize the parts in the CT volume using CAD data, precise alignment of the two data sets is necessary. However, the shape of real products may be different from the design because of a modification during manufacturing or deformation by assemble. This shape deviation between the two data makes an automated alignment difficult. With this reason, currently, the alignment of CAD data and CT scanned data is conducted depending on the human eye, and it increases time and human costs, and the results highly depend on the operator. In this study, we propose an algorithm to align a CAD mesh and a CT volume with a higher precision than an existing algorithm. The proposed algorithm first extracts a surface mesh from the CT volume, and then move the CAD mesh so that it matches the extracted mesh by the transformation computed by an optimization regarding the vertex positions and the orientations of the normal vectors of the CAD mesh and the gradient vectors of the CT values. Experiments show that the proposed algorithm achieved the alignment accuracy in average almost same as the voxel size.