Image segmentation for laser triangulation based on Chan-Vese model

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autorschaft

  • T. Mueller
  • E. Reithmeier
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Details

OriginalspracheEnglisch
Seiten (von - bis)100-109
Seitenumfang10
FachzeitschriftMeasurement
Jahrgang63
PublikationsstatusVeröffentlicht - 12 Dez. 2014

Abstract

Laser triangulation is a well-established technique in 3D surface metrology. However, scattering surfaces and reflectivity variations cause measurement uncertainties due to a reduced signal-to-noise ratio. To improve the measurement accuracy of such surfaces a new laser line detection algorithm is proposed. Within this work, the laser line segmentation and, therefore, the separation of the laser line and the noisy background in the camera images are based on the Chan-Vese model. The Chan-Vese model is adapted to reduce the computation time and increase the measurement rate, which is important in industrial applications. In this paper, complete instructions on how to apply the Chan-Vese segmentation algorithm to laser line triangulation measurements are given, including initialization and a parameter set for the segmentation process. Further, an example of laser triangulation measurement of a microstructured, highly scattering surface is presented. Closing, the proposed approach is compared with a conventional line detection method.

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Image segmentation for laser triangulation based on Chan-Vese model. / Mueller, T.; Reithmeier, E.
in: Measurement, Jahrgang 63, 12.12.2014, S. 100-109.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Mueller T, Reithmeier E. Image segmentation for laser triangulation based on Chan-Vese model. Measurement. 2014 Dez 12;63:100-109. doi: 10.1016/j.measurement.2014.12.007
Mueller, T. ; Reithmeier, E. / Image segmentation for laser triangulation based on Chan-Vese model. in: Measurement. 2014 ; Jahrgang 63. S. 100-109.
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AU - Reithmeier, E.

N1 - Funding information: This work was sponsored by the Federal Ministry of Education and Research (BMBF). The project reference code is 03V0473. The author is responsible for the content of this publication.

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