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

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OriginalspracheEnglisch
Titel des SammelwerksAutomated Visual Inspection and Machine Vision IV
Herausgeber/-innenJurgen Beyerer, Michael Heizmann
Herausgeber (Verlag)SPIE
Seitenumfang11
ISBN (elektronisch)9781510644083
PublikationsstatusVeröffentlicht - 20 Juni 2021
VeranstaltungSPIE Optical Metrology
- Online
Dauer: 21 Juni 202125 Juni 2021
https://spie.org/conferences-and-exhibitions/optical-metrology?SSO=1

Publikationsreihe

NameProceedings of SPIE - The International Society for Optical Engineering
Band11787
ISSN (Print)0277-786X
ISSN (elektronisch)1996-756X

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 TorrenceSparrow 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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A GPU-based ray tracing approach for the prediction of multireflections on measurement objects and the a priori estimation of low-reflection measurement poses. / Middendorf, Philipp; Kern, Pascal; Melchert, Nils Frederik et al.
Automated Visual Inspection and Machine Vision IV. Hrsg. / Jurgen Beyerer; Michael Heizmann. SPIE, 2021. 117870B (Proceedings of SPIE - The International Society for Optical Engineering; Band 11787).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschung

Middendorf, P, Kern, P, Melchert, NF, Kästner, M & Reithmeier, E 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. in J Beyerer & M Heizmann (Hrsg.), Automated Visual Inspection and Machine Vision IV., 117870B, Proceedings of SPIE - The International Society for Optical Engineering, Bd. 11787, SPIE, SPIE Optical Metrology
, 21 Juni 2021. https://doi.org/10.1117/12.2592565
Middendorf, P., Kern, P., Melchert, N. F., Kästner, M., & Reithmeier, E. (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. In J. Beyerer, & M. Heizmann (Hrsg.), Automated Visual Inspection and Machine Vision IV Artikel 117870B (Proceedings of SPIE - The International Society for Optical Engineering; Band 11787). SPIE. https://doi.org/10.1117/12.2592565
Middendorf P, Kern P, Melchert NF, Kästner M, Reithmeier E. A GPU-based ray tracing approach for the prediction of multireflections on measurement objects and the a priori estimation of low-reflection measurement poses. in Beyerer J, Heizmann M, Hrsg., Automated Visual Inspection and Machine Vision IV. SPIE. 2021. 117870B. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2592565
Middendorf, Philipp ; Kern, Pascal ; Melchert, Nils Frederik et al. / A GPU-based ray tracing approach for the prediction of multireflections on measurement objects and the a priori estimation of low-reflection measurement poses. Automated Visual Inspection and Machine Vision IV. Hrsg. / Jurgen Beyerer ; Michael Heizmann. SPIE, 2021. (Proceedings of SPIE - The International Society for Optical Engineering).
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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 TorrenceSparrow 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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AU - Kern, Pascal

AU - Melchert, Nils Frederik

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