Application of an edge detection algorithm for surface determination in industrial X‑ray computed tomography

Busch M, Hausotte T (2022)


Publication Language: English

Publication Type: Journal article, other

Publication year: 2022

Journal

DOI: 10.1007/s11740-021-01100-z

Abstract

Surface determination is an essential step of the measurement process in industrial X-ray computed tomography (XCT). The starting point of the surface determination process step is a single grey value threshold within a voxel volume in conventional surface determination methods. However, this value is not always found in the reconstructed volume in the local environment of the surface of the measurement object due to various artefacts, so that none or incorrect surfaces are determined. In order to find surfaces independently of a single grey value, a three-dimensional approach of the initial contour determination based on a Prewitt edge detection algorithm is presented in this work. This method is applied to different test specimens and specimen compositions which, due to their material or material constellation, their geometric properties with regard to surfaces and interfaces as well as their calibrated size and length dimensions, embody relevant properties in the examination of joining connections. It is shown that by using the surface determination method in the measurement process, both a higher metrological structure resolution and interface structure resolution can be achieved. Surface artefacts can be reduced by the application and it is also an approach to improved surface finding for the multi-material components that are challenging for XCT.

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How to cite

APA:

Busch, M., & Hausotte, T. (2022). Application of an edge detection algorithm for surface determination in industrial X‑ray computed tomography. Production Engineering. https://dx.doi.org/10.1007/s11740-021-01100-z

MLA:

Busch, Matthias, and Tino Hausotte. "Application of an edge detection algorithm for surface determination in industrial X‑ray computed tomography." Production Engineering (2022).

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