A GPU-based ray tracing approach for the prediction of multireflections on measurement objects and the a priori estimation of low-reflection measurement poses

Philipp Middendorf; Pascal Kern; Nils Melchert; Markus Kästner; Eduard Reithmeier

doi:10.1117/12.2592565

20 June 2021 A GPU-based ray tracing approach for the prediction of multireflections on measurement objects and the a priori estimation of low-reflection measurement poses

Philipp Middendorf, Pascal Kern, Nils Melchert, Markus Kästner, Eduard Reithmeier

Author Affiliations +

Proceedings Volume 11787, Automated Visual Inspection and Machine Vision IV; 117870B (2021) https://doi.org/10.1117/12.2592565
Event: SPIE Optical Metrology, 2021, Online Only

Abstract

For the automated optical inspection of manufactured components with complex geometries or highly reflective surfaces, a suitable selection of measurement poses and the associated planning of the measurement trajectory is crucial. This is especially important for active triangulation measurement methods like fringe projection. Due to complex measurement object geometries or poor alignment of the measuring system the influence of multiple reflections can potentially lead to incorrect or incomplete 3-D reconstruction of the specimen surface. This paper introduces a simulative GPU-based inverse ray tracing approach to identify low-reflection measurement poses for active optical measurement systems. Starting from the virtual camera origin, rays are emitted from each camera pixel and the reflection at the measurement objects surface is calculated using the Torrence- Sparrow BRDF. With an additional approach based on Whitted raytracing, the influence of multiple reflections and the reflection depth on the rendered camera image is taken into account. By calculating the summed reflection depth of each rendered measurement sequence, a height map of the reflection frequency distribution is created. By sampling a predefined surface point on the path of a limited sphere, the comparability of possible measurement poses is achieved. Thus, local minima can be identified and the poses with the lowest reflection influence can be selected to perform a suitable trajectory planning. This a priori knowledge can also be transferred into application and used for the estimation of image areas, which captured multiple reflections. Thus for these areas specific masks are generated and can be applied in real measurements to reconstruct multiple reflection free surfaces.

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Philipp Middendorf, Pascal Kern, Nils Melchert, Markus Kästner, and Eduard Reithmeier "A GPU-based ray tracing approach for the prediction of multireflections on measurement objects and the a priori estimation of low-reflection measurement poses", Proc. SPIE 11787, Automated Visual Inspection and Machine Vision IV, 117870B (20 June 2021); https://doi.org/10.1117/12.2592565

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