Abstract
One task of industrial computed tomography in dimensional metrology is to provide surface models of examined objects. Currently, in the standard approach polygonal surface meshes from reconstructed tomograms are extracted. Precise surface meshes require a high resolution tomogram, leading to time-consuming reconstruction algorithms. In order to overcome this problem, we propose a method to approximate the contour by a point cloud of folds, which resemble the most characteristic parts of the object. These creases are reconstructed from filtered projection images directly in Cartesian space. This cloud of creases will serve as a basis for the creation of meshes. Initial results of a 2D phantom study indicate that the method reaches reconstruction accuracies comparable to standard methods while the number of necessary projections is reduced significantly, leading to a notable decrease in scan time.
| Original language | English |
|---|---|
| Journal | e-Journal of Nondestructive Testing |
| Volume | 2019-03 |
| Number of pages | 1 |
| Publication status | Published - 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
-
SDG 9 Industry, Innovation, and Infrastructure
Fingerprint
Dive into the research topics of '2D Contour Reconstruction for Industrial Computed Tomography using Crease Cluster'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver