A flexible and simplified calibration procedure for fringe projection profilometry

Fringe Projection Profilometry (FPP) is a widely used technique for optical three-dimensional (3D) shape measurement. Among the existing 3D shape measurement techniques, FPP provides a whole-field 3D reconstruction of objects in a non-contact manner, with high resolution, and fast data processing. T...

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Tipo de recurso:
Fecha de publicación:
2019
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/9171
Acceso en línea:
https://hdl.handle.net/20.500.12585/9171
Palabra clave:
3D shape measurement
Calibration
Fringe projection profilometry
Calibration
Data handling
Inverse problems
Mapping
Profilometry
Stereo image processing
Stereo vision
3-d shape measurement
Calibration procedure
Fringe projection profilometry
Low computational complexity
Reconstruction process
Simplified calibrations
Three dimensional (3 D) shape measurement
Triangulation principles
Image reconstruction
Rights
restrictedAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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repository_id_str
dc.title.none.fl_str_mv A flexible and simplified calibration procedure for fringe projection profilometry
title A flexible and simplified calibration procedure for fringe projection profilometry
spellingShingle A flexible and simplified calibration procedure for fringe projection profilometry
3D shape measurement
Calibration
Fringe projection profilometry
Calibration
Data handling
Inverse problems
Mapping
Profilometry
Stereo image processing
Stereo vision
3-d shape measurement
Calibration procedure
Fringe projection profilometry
Low computational complexity
Reconstruction process
Simplified calibrations
Three dimensional (3 D) shape measurement
Triangulation principles
Image reconstruction
title_short A flexible and simplified calibration procedure for fringe projection profilometry
title_full A flexible and simplified calibration procedure for fringe projection profilometry
title_fullStr A flexible and simplified calibration procedure for fringe projection profilometry
title_full_unstemmed A flexible and simplified calibration procedure for fringe projection profilometry
title_sort A flexible and simplified calibration procedure for fringe projection profilometry
dc.contributor.editor.none.fl_str_mv Bodermann B.
Frenner K.
dc.subject.keywords.none.fl_str_mv 3D shape measurement
Calibration
Fringe projection profilometry
Calibration
Data handling
Inverse problems
Mapping
Profilometry
Stereo image processing
Stereo vision
3-d shape measurement
Calibration procedure
Fringe projection profilometry
Low computational complexity
Reconstruction process
Simplified calibrations
Three dimensional (3 D) shape measurement
Triangulation principles
Image reconstruction
topic 3D shape measurement
Calibration
Fringe projection profilometry
Calibration
Data handling
Inverse problems
Mapping
Profilometry
Stereo image processing
Stereo vision
3-d shape measurement
Calibration procedure
Fringe projection profilometry
Low computational complexity
Reconstruction process
Simplified calibrations
Three dimensional (3 D) shape measurement
Triangulation principles
Image reconstruction
description Fringe Projection Profilometry (FPP) is a widely used technique for optical three-dimensional (3D) shape measurement. Among the existing 3D shape measurement techniques, FPP provides a whole-field 3D reconstruction of objects in a non-contact manner, with high resolution, and fast data processing. The key to accurate 3D shape measurement is the proper calibration of the measurement system. Currently, most calibration procedures in FPP rely on phase-coordinate mapping (PCM) or back-projection stereo-vision (SV) methods. The PCM technique consists in mapping experimental metric XYZ coordinates to recovered phase values by fitting a predetermined function. However, it requires accurately placing 2D or 3D targets at different distances and orientations. Conversely, in the SV method, the projector is regarded as an inverse camera, and the system is modeled using triangulation principles. Therefore, the calibration process can be carried out using 2D targets placed in arbitrary positions and orientations, resulting in a more flexible procedure. In this work, we propose a hybrid calibration procedure that combines SV and PCM methods. The procedure is highly flexible, robust to lens distortions, and has a simple relationship between phase and coordinates. Experimental results show that the proposed method has advantages over the conventional SV model since it needs fewer acquired images for the reconstruction process, and due to its low computational complexity the reconstruction time decreases significantly. © 2019 SPIE.
publishDate 2019
dc.date.issued.none.fl_str_mv 2019
dc.date.accessioned.none.fl_str_mv 2020-03-26T16:33:07Z
dc.date.available.none.fl_str_mv 2020-03-26T16:33:07Z
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dc.type.spa.none.fl_str_mv Conferencia
status_str publishedVersion
dc.identifier.citation.none.fl_str_mv Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11057
dc.identifier.isbn.none.fl_str_mv 9781510627932
dc.identifier.issn.none.fl_str_mv 0277786X
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/9171
dc.identifier.doi.none.fl_str_mv 10.1117/12.2527607
dc.identifier.instname.none.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.none.fl_str_mv Repositorio UTB
dc.identifier.orcid.none.fl_str_mv 57117284600
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57192270016
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identifier_str_mv Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11057
9781510627932
0277786X
10.1117/12.2527607
Universidad Tecnológica de Bolívar
Repositorio UTB
57117284600
24329839300
57192270016
36142156300
url https://hdl.handle.net/20.500.12585/9171
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.conferencedate.none.fl_str_mv 24 June 2019 through 26 June 2019
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.rights.uri.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.rights.cc.none.fl_str_mv Atribución-NoComercial 4.0 Internacional
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Atribución-NoComercial 4.0 Internacional
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dc.format.medium.none.fl_str_mv Recurso electrónico
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dc.publisher.none.fl_str_mv SPIE
publisher.none.fl_str_mv SPIE
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dc.source.event.none.fl_str_mv Modeling Aspects in Optical Metrology VII 2019
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spelling Bodermann B.Frenner K.Vargas R.Marrugo A.G.Pineda J.Romero L.A.2020-03-26T16:33:07Z2020-03-26T16:33:07Z2019Proceedings of SPIE - The International Society for Optical Engineering; Vol. 1105797815106279320277786Xhttps://hdl.handle.net/20.500.12585/917110.1117/12.2527607Universidad Tecnológica de BolívarRepositorio UTB57117284600243298393005719227001636142156300Fringe Projection Profilometry (FPP) is a widely used technique for optical three-dimensional (3D) shape measurement. Among the existing 3D shape measurement techniques, FPP provides a whole-field 3D reconstruction of objects in a non-contact manner, with high resolution, and fast data processing. The key to accurate 3D shape measurement is the proper calibration of the measurement system. Currently, most calibration procedures in FPP rely on phase-coordinate mapping (PCM) or back-projection stereo-vision (SV) methods. The PCM technique consists in mapping experimental metric XYZ coordinates to recovered phase values by fitting a predetermined function. However, it requires accurately placing 2D or 3D targets at different distances and orientations. Conversely, in the SV method, the projector is regarded as an inverse camera, and the system is modeled using triangulation principles. Therefore, the calibration process can be carried out using 2D targets placed in arbitrary positions and orientations, resulting in a more flexible procedure. In this work, we propose a hybrid calibration procedure that combines SV and PCM methods. The procedure is highly flexible, robust to lens distortions, and has a simple relationship between phase and coordinates. Experimental results show that the proposed method has advantages over the conventional SV model since it needs fewer acquired images for the reconstruction process, and due to its low computational complexity the reconstruction time decreases significantly. © 2019 SPIE.Universidad Tecnológica de Pereira, UTP: C2018P018, C2018P005 Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS), COLCIENCIAS 538871552485The Society of Photo-Optical Instrumentation Engineers (SPIE)This work has been partly funded by Colciencias (Fondo Nacional de Financiamiento para la Ciencia, la Tec-nología y la Innovación Francisco Joséde Caldas) project 538871552485, and by Universidad Tecnológica de Bolívar projects C2018P005 and C2018P018. J. Pineda and R. Vargas thank Universidad Tecnológica de Bolívar for a post-graduate scholarship.Recurso electrónicoapplication/pdfengSPIEhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85072571081&doi=10.1117%2f12.2527607&partnerID=40&md5=b56098f8e33661496c853dc7e3cd7408Scopus2-s2.0-85072571081Modeling Aspects in Optical Metrology VII 2019A flexible and simplified calibration procedure for fringe projection profilometryinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94f3D shape measurementCalibrationFringe projection profilometryCalibrationData handlingInverse problemsMappingProfilometryStereo image processingStereo vision3-d shape measurementCalibration procedureFringe projection profilometryLow computational complexityReconstruction processSimplified calibrationsThree dimensional (3 D) shape measurementTriangulation principlesImage reconstruction24 June 2019 through 26 June 2019Marrugo, A.G., Pineda, J., Romero, L.A., Vargas, R., Meneses, J., Fourier transform profilometry in labview (2018) Digital Systems, , IntechOpenGorthi, S.S., Rastogi, P., Fringe projection techniques: Whither we are? (2010) Optics and Lasers in Engi-Neering, 48 (2), pp. 133-140Cai, Z., Liu, X., Li, A., Tang, Q., Peng, X., Gao, B.Z., Phase-3d mapping method developed from back-projection stereovision model for fringe projection profilometry (2017) Optics Express, 25 (2), pp. 1262-1277Vargas, R., Marrugo, A.G., Pineda, J., Meneses, J., Romero, L.A., Camera-projector calibration methods with compensation of geometric distortions in fringe projection profilometry: A comparative study (2018) Opt. Pura Apl., 51 (3)Vo, M., Wang, Z., Hoang, T., Nguyen, D., Flexible calibration technique for fringe-projection-based three-dimensional imaging (2010) Optics Letters, 35 (19), pp. 3192-3194Huang, L., Chua, P.S., Asundi, A., Least-squares calibration method for fringe projection profilometry considering camera lens distortion (2010) Applied Optics, 49 (9), pp. 1539-1548Zhang, S., Huang, P.S., Novel method for structured light system calibration (2006) Optical Engineering, 45 (8), p. 083601Vargas, R., Marrugo, A.G., Pineda, J., Meneses, J., Romero, L.A., Evaluating the inuence of camera and projector lens distortion in 3d reconstruction quality for fringe projection profilometry (2018) Imaging and Applied Optics 2018, , 3M3G.5, OSA, Washington, D.CPineda, J., Vargas, R., Romero, L.A., Meneses, J., Marrugo, A.G., Fringe quality map for fringe projection profilometry in LabVIEW (2018) Opt. Pura Apl., 51 (4), pp. 503021-503028Li, Z., Shi, Y., Wang, C., Wang, Y., Accurate calibration method for a structured light system (2008) Optical Engineering, 47 (5), p. 053604Luo, H., Xu, J., Binh, N.H., Liu, S., Zhang, C., Chen, K., A simple calibration procedure for structured light system (2014) Optics and Lasers in Engineering, 57, pp. 6-12Li, K., Bu, J., Zhang, D., Lens distortion elimination for improving measurement accuracy of fringe projection profilometry (2016) Optics and Lasers in Engineering, 85, pp. 53-64Bouguet, J.-Y., (2008) Camera Calibration Toolbox for Matlab (2008), , http://www.vision.caltech.edu/bouguetj/calibdoc1080Lagarias, J.C., Reeds, J.A., Wright, M.H., Wright, P.E., Convergence properties of the nelder-mead simplex method in low dimensions (1998) SIAM Journal on Optimization, 9 (1), pp. 112-147http://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/9171/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/9171oai:repositorio.utb.edu.co:20.500.12585/91712021-02-02 15:29:52.213Repositorio Institucional UTBrepositorioutb@utb.edu.co