Image segmentation for laser triangulation based on Chan–Vese model

• A novel data processing algorithm for laser triangulation on highly scattering surfaces is presented.
• The processing algorithm uses image segmentation based on the Chan–Vese model.
• Data segmentation highly increases the measurement accuracy for scattering surfaces.
• A speed up method for the Chan–Vese segmentation based on linear extrapolation is presented.

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.