Fleßner M, Müller A, Helmecke E, Hausotte T (2015)
Publication Type: Conference contribution
Publication year: 2015
Conference Proceedings Title: Digital Industrial Radiology and Computed Tomography
Open Access Link: http://www.ndt.net/events/DIR2015/app/content/Paper/35_Flesner.pdf
Artefacts within CT volume data have a large impact on the results of dimensional measurements. To avoid measurement deviations, it is therefore crucial to identify regions affected by artefacts. The presented method analyses the volume data in the proximity of an extracted surface point to calculate a Local Quality Value (LQV). Using this method, surface points affected by artefacts are identified and highlighted in 2D and 3D visualisations. As only the volume data and the extracted surface are required to calculate the LQV, no additional knowledge like a CAD model or a reference measurement is necessary and the analysis can be carried out automatically. CT scans of calibrated gauges blocks that exhibit large errors in the segmented surface dataset due to artefacts are used to demonstrate the capability of the presented method. It is shown that it is possible to increase the accuracy of dimensional measurements by considering the information provided by the LQV.
Fleßner, M., Müller, A., Helmecke, E., & Hausotte, T. (2015). Automated detection of artefacts for computed tomography in dimensional metrology. In Digital Industrial Radiology and Computed Tomography. Gent, BE.
Fleßner, Matthias, et al. "Automated detection of artefacts for computed tomography in dimensional metrology." Proceedings of the International Symposium on Digital Industrial Radiology and Computed Tomography (DIR 2015), Gent 2015.