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Improved defect segmentation by combining fiber optic fringe projection profilometry with directional variable brightfield illumination

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

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Details

OriginalspracheEnglisch
Titel des SammelwerksEmerging Digital Micromirror Device Based Systems and Applications XIII
Herausgeber/-innenJohn Ehmke, Benjamin L. Lee
Herausgeber (Verlag)SPIE
ISBN (elektronisch)9781510642317
PublikationsstatusVeröffentlicht - 2021
VeranstaltungEmerging Digital Micromirror Device Based Systems and Applications XIII 2021 - Virtual, Online, USA / Vereinigte Staaten
Dauer: 6 März 202111 März 2021

Publikationsreihe

NameProceedings of SPIE - The International Society for Optical Engineering
Band11698
ISSN (Print)0277-786X
ISSN (elektronisch)1996-756X

Abstract

Based the fringe projection profilometry, a compact and flexible positionable measuring head can be combined with optical fiber bundles to perform in-situ inspection tasks in industrial applications. Surfaces of complex geometries can be reconstructed and quantified in metric coordinates by means of a fast, non-contact and high-resolution measurement. Defect segmentation, on the other hand, is rather complex with three-dimensional point clouds, since reference data is required or a deviation determination is ambiguous and susceptible to errors. Due to each reconstructed object point corresponding to a camera pixel, it is possible to apply image processing algorithms or neural networks for defect segmentation. Since image based segmentation is more susceptible to poor illumination and deviating surface curvature or texture, a circular array of miniature LEDs has been coaxially arranged around the imaging optics of the camera's fiber to provide different illumination directions. By utilizing a directional variable illumination sequence, the advantages of image-based segmentation can be combined with the unambiguousness and metric quantifiability of point cloud data.

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Improved defect segmentation by combining fiber optic fringe projection profilometry with directional variable brightfield illumination. / Hinz, Lennart; Kästner, Markus; Reithmeier, Eduard.
Emerging Digital Micromirror Device Based Systems and Applications XIII. Hrsg. / John Ehmke; Benjamin L. Lee. SPIE, 2021. 116980S (Proceedings of SPIE - The International Society for Optical Engineering; Band 11698).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Hinz, L, Kästner, M & Reithmeier, E 2021, Improved defect segmentation by combining fiber optic fringe projection profilometry with directional variable brightfield illumination. in J Ehmke & BL Lee (Hrsg.), Emerging Digital Micromirror Device Based Systems and Applications XIII., 116980S, Proceedings of SPIE - The International Society for Optical Engineering, Bd. 11698, SPIE, Emerging Digital Micromirror Device Based Systems and Applications XIII 2021, Virtual, Online, USA / Vereinigte Staaten, 6 März 2021. https://doi.org/10.1117/12.2578564
Hinz, L., Kästner, M., & Reithmeier, E. (2021). Improved defect segmentation by combining fiber optic fringe projection profilometry with directional variable brightfield illumination. In J. Ehmke, & B. L. Lee (Hrsg.), Emerging Digital Micromirror Device Based Systems and Applications XIII Artikel 116980S (Proceedings of SPIE - The International Society for Optical Engineering; Band 11698). SPIE. https://doi.org/10.1117/12.2578564
Hinz L, Kästner M, Reithmeier E. Improved defect segmentation by combining fiber optic fringe projection profilometry with directional variable brightfield illumination. in Ehmke J, Lee BL, Hrsg., Emerging Digital Micromirror Device Based Systems and Applications XIII. SPIE. 2021. 116980S. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2578564
Hinz, Lennart ; Kästner, Markus ; Reithmeier, Eduard. / Improved defect segmentation by combining fiber optic fringe projection profilometry with directional variable brightfield illumination. Emerging Digital Micromirror Device Based Systems and Applications XIII. Hrsg. / John Ehmke ; Benjamin L. Lee. SPIE, 2021. (Proceedings of SPIE - The International Society for Optical Engineering).
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Download

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AU - Hinz, Lennart

AU - Kästner, Markus

AU - Reithmeier, Eduard

N1 - Funding Information: The authors would like to thank the German Research Foundation (DFG) for funding the project B6 ”Endoscopic geometry inspection” within the Collaborative Research Center (CRC) / TR 73.

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N2 - Based the fringe projection profilometry, a compact and flexible positionable measuring head can be combined with optical fiber bundles to perform in-situ inspection tasks in industrial applications. Surfaces of complex geometries can be reconstructed and quantified in metric coordinates by means of a fast, non-contact and high-resolution measurement. Defect segmentation, on the other hand, is rather complex with three-dimensional point clouds, since reference data is required or a deviation determination is ambiguous and susceptible to errors. Due to each reconstructed object point corresponding to a camera pixel, it is possible to apply image processing algorithms or neural networks for defect segmentation. Since image based segmentation is more susceptible to poor illumination and deviating surface curvature or texture, a circular array of miniature LEDs has been coaxially arranged around the imaging optics of the camera's fiber to provide different illumination directions. By utilizing a directional variable illumination sequence, the advantages of image-based segmentation can be combined with the unambiguousness and metric quantifiability of point cloud data.

AB - Based the fringe projection profilometry, a compact and flexible positionable measuring head can be combined with optical fiber bundles to perform in-situ inspection tasks in industrial applications. Surfaces of complex geometries can be reconstructed and quantified in metric coordinates by means of a fast, non-contact and high-resolution measurement. Defect segmentation, on the other hand, is rather complex with three-dimensional point clouds, since reference data is required or a deviation determination is ambiguous and susceptible to errors. Due to each reconstructed object point corresponding to a camera pixel, it is possible to apply image processing algorithms or neural networks for defect segmentation. Since image based segmentation is more susceptible to poor illumination and deviating surface curvature or texture, a circular array of miniature LEDs has been coaxially arranged around the imaging optics of the camera's fiber to provide different illumination directions. By utilizing a directional variable illumination sequence, the advantages of image-based segmentation can be combined with the unambiguousness and metric quantifiability of point cloud data.

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