3D Segmentation of CT Volumetric Image for Mechanical Assemblies with Forcible Edge Enhancement

We propose a new segmentation method for separating parts of a mechanical assembly in a CT volumetric image. Part segmentation is generally based on edge detection with gradient norms of the CT volumetric image, which often fails when parts made of the same material come into close contact. This is because an image is blurry between the parts with low gradient norms and indistinct edges. In order to enhance weak edges at such faded part boundaries, our idea is to enhance the gradient norm in a CT volumetric image. To find such faded boundaries, auxiliary information needs to be introduced. In this paper, two practical cases of the faded boundaries in plastic and welded assemblies of sheet metal parts are studied. For the former case, CAD mesh models of target parts are used. The faded boundaries are found in blurred regions on the CAD mesh boundaries. For the latter case, the thickness value of the sheet metal parts used, and it is assumed to be constant. The faded boundary can be located at the distance of the thickness from the outer surface of the part. By enhancing the gradient norms in those faded boundaries, the assembly of parts made of the same material can be segmented. The algorithms are implemented, and experimental results are demonstrated.