Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : September 15, 2021 - September 17, 2021
Industrial X-ray CT is nowadays an essential tool to inspect industrial assembly without disassembling. However, these CT volumes are usually composed of a huge number of voxels without any information representing its parts, which prohibits visualizing only the parts that the users are interested in. On the other hand, it is considered effective for this problem to leverage geometric features extracted from the CT volume. According to this thought, this paper introduces a new geometric attribute, which we refer to as a degree of local geometry (DLS), involved with each voxel and investigates on its effect for visualizing CT volume. The DLS represents a dimensionality of the manifold around a voxel, e.g., that for a surface will be 2. We experiment its effect in visualizing CT data by installing the DLS on voxels into a sparse voxel octree (SVO), which significantly reduces data size and computational complexity. we demonstrate that the DLS works significantly well to selectively visualize small parts inside several test assemblies, such as a set of primitive shapes and a radio-controlled car.
