Background intensity removal in structured light three-dimensional reconstruction

In Fourier Transform Profilometry, a filtering procedure is performed to separate the desired information (first order spectrum) from other unwanted contributions such as the background component (zero-order spectrum). However, if the zero-order spectrum and the high order spectra component interfer...

Full description

Autores:
Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/8976
Acceso en línea:
https://hdl.handle.net/20.500.12585/8976
Palabra clave:
Contour measurement
Image processing
Information filtering
Mathematical morphology
Mathematical transformations
Profilometry
Vision
Background components
Bi-dimensional empirical mode decompositions
Filtering procedures
Fourier transform profilometry
High order spectra
Morphological operations
Sequential combination
Three-dimensional reconstruction
Signal processing
Rights
restrictedAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
id UTB2_a9db33cab3b9bc50a37489210ee1f664
oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/8976
network_acronym_str UTB2
network_name_str Repositorio Institucional UTB
repository_id_str
dc.title.none.fl_str_mv Background intensity removal in structured light three-dimensional reconstruction
title Background intensity removal in structured light three-dimensional reconstruction
spellingShingle Background intensity removal in structured light three-dimensional reconstruction
Contour measurement
Image processing
Information filtering
Mathematical morphology
Mathematical transformations
Profilometry
Vision
Background components
Bi-dimensional empirical mode decompositions
Filtering procedures
Fourier transform profilometry
High order spectra
Morphological operations
Sequential combination
Three-dimensional reconstruction
Signal processing
title_short Background intensity removal in structured light three-dimensional reconstruction
title_full Background intensity removal in structured light three-dimensional reconstruction
title_fullStr Background intensity removal in structured light three-dimensional reconstruction
title_full_unstemmed Background intensity removal in structured light three-dimensional reconstruction
title_sort Background intensity removal in structured light three-dimensional reconstruction
dc.contributor.editor.none.fl_str_mv Altuve M.
dc.subject.keywords.none.fl_str_mv Contour measurement
Image processing
Information filtering
Mathematical morphology
Mathematical transformations
Profilometry
Vision
Background components
Bi-dimensional empirical mode decompositions
Filtering procedures
Fourier transform profilometry
High order spectra
Morphological operations
Sequential combination
Three-dimensional reconstruction
Signal processing
topic Contour measurement
Image processing
Information filtering
Mathematical morphology
Mathematical transformations
Profilometry
Vision
Background components
Bi-dimensional empirical mode decompositions
Filtering procedures
Fourier transform profilometry
High order spectra
Morphological operations
Sequential combination
Three-dimensional reconstruction
Signal processing
description In Fourier Transform Profilometry, a filtering procedure is performed to separate the desired information (first order spectrum) from other unwanted contributions such as the background component (zero-order spectrum). However, if the zero-order spectrum and the high order spectra component interfere the fundamental spectra, the 3D reconstruction precision decreases. In this paper, we test two recently proposed methods for removing the background intensity so as to improve Fourier Transform Profilometry reconstruction precision. The first method is based on the twice piece-wise Hilbert transform. The second is based on Bidimensional Empirical Mode Decomposition, but the decomposition is carried out by morphological operations In this work, we present as a novel contribution, the sequential combination of these two methods for removing the background intensity and other unwanted frequencies close to the first order spectrum, thus obtaining the 3D topography of the object. Encouraging experimental results show the advantage of the proposed method. © 2016 IEEE.
publishDate 2016
dc.date.issued.none.fl_str_mv 2016
dc.date.accessioned.none.fl_str_mv 2020-03-26T16:32:42Z
dc.date.available.none.fl_str_mv 2020-03-26T16:32:42Z
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_c94f
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/conferenceObject
dc.type.hasVersion.none.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.spa.none.fl_str_mv Conferencia
status_str publishedVersion
dc.identifier.citation.none.fl_str_mv 2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
dc.identifier.isbn.none.fl_str_mv 9781509037971
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/8976
dc.identifier.doi.none.fl_str_mv 10.1109/STSIVA.2016.7743326
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
57192270016
24329839300
36142156300
identifier_str_mv 2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
9781509037971
10.1109/STSIVA.2016.7743326
Universidad Tecnológica de Bolívar
Repositorio UTB
57117284600
57192270016
24329839300
36142156300
url https://hdl.handle.net/20.500.12585/8976
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.conferencedate.none.fl_str_mv 30 August 2016 through 2 September 2016
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/
dc.rights.accessRights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
dc.rights.cc.none.fl_str_mv Atribución-NoComercial 4.0 Internacional
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Atribución-NoComercial 4.0 Internacional
http://purl.org/coar/access_right/c_16ec
eu_rights_str_mv restrictedAccess
dc.format.medium.none.fl_str_mv Recurso electrónico
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
dc.source.none.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-85002980258&doi=10.1109%2fSTSIVA.2016.7743326&partnerID=40&md5=da38e732664072c4c61c6bb0219286df
Scopus2-s2.0-85002980258
institution Universidad Tecnológica de Bolívar
dc.source.event.none.fl_str_mv 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
bitstream.url.fl_str_mv https://repositorio.utb.edu.co/bitstream/20.500.12585/8976/1/MiniProdInv.png
bitstream.checksum.fl_str_mv 0cb0f101a8d16897fb46fc914d3d7043
bitstream.checksumAlgorithm.fl_str_mv MD5
repository.name.fl_str_mv Repositorio Institucional UTB
repository.mail.fl_str_mv repositorioutb@utb.edu.co
_version_ 1814021688989319168
spelling Altuve M.Vargas R.Pineda J.Marrugo A.G.Romero L.A.2020-03-26T16:32:42Z2020-03-26T16:32:42Z20162016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 20169781509037971https://hdl.handle.net/20.500.12585/897610.1109/STSIVA.2016.7743326Universidad Tecnológica de BolívarRepositorio UTB57117284600571922700162432983930036142156300In Fourier Transform Profilometry, a filtering procedure is performed to separate the desired information (first order spectrum) from other unwanted contributions such as the background component (zero-order spectrum). However, if the zero-order spectrum and the high order spectra component interfere the fundamental spectra, the 3D reconstruction precision decreases. In this paper, we test two recently proposed methods for removing the background intensity so as to improve Fourier Transform Profilometry reconstruction precision. The first method is based on the twice piece-wise Hilbert transform. The second is based on Bidimensional Empirical Mode Decomposition, but the decomposition is carried out by morphological operations In this work, we present as a novel contribution, the sequential combination of these two methods for removing the background intensity and other unwanted frequencies close to the first order spectrum, thus obtaining the 3D topography of the object. Encouraging experimental results show the advantage of the proposed method. © 2016 IEEE.Universidad Pontificia Bolivariana (UPB) Seccional BucaramangaRecurso electrónicoapplication/pdfengInstitute of Electrical and Electronics Engineers Inc.http://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-s2.0-85002980258&doi=10.1109%2fSTSIVA.2016.7743326&partnerID=40&md5=da38e732664072c4c61c6bb0219286dfScopus2-s2.0-8500298025821st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016Background intensity removal in structured light three-dimensional reconstructioninfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fContour measurementImage processingInformation filteringMathematical morphologyMathematical transformationsProfilometryVisionBackground componentsBi-dimensional empirical mode decompositionsFiltering proceduresFourier transform profilometryHigh order spectraMorphological operationsSequential combinationThree-dimensional reconstructionSignal processing30 August 2016 through 2 September 2016Federico, A., Kaufmann, G.H., Phase retrieval in digital speckle pattern interferometry by use of a smoothed space-frequency distribution (2003) Applied Optics, 42 (35), pp. 7066-7071Ǵomez, A.L.G., Fonseca, J.E.M., Téllez, J.L., Proyeccíon de franjas en metroloǵa optica facial (2012) INGE CUC, 8 (1), pp. 191-206Guan, C., Hassebrook, L., Lau, D., Composite structured light pattern for three-dimensional video (2003) Optics Express, 11 (5), pp. 406-417Guo, H., (2009) 3-D Shape Measurement Based on Fourier Transform and Phase Shifting Method, , PhD thesis, STATE UNIVERSITY OF New York AT STONY BROOKHuang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.C., Liu, H.H., The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis (1998) Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 454 (1971), pp. 903-995. , MarKemao, Q., Windowed fourier transform for fringe pattern analysis (2004) Applied Optics, 43 (13), pp. 2695-2702Luo, F., Chen, W., Su, X., Eliminating zero spectra in fourier transform profilometry by application of hilbert transform (2016) Optics Communications, 365, pp. 76-85Nunes, J.C., Bouaoune, Y., Delechelle, E., Niang, O., Bunel, P., Image analysis by bidimensional empirical mode decomposition (2003) Image and Vision Computing, 21 (12), pp. 1019-1026Su, X., Chen, W., Fourier transform profilometry:: A review (2001) Optics and Lasers in EngineeringSu, X., Chen, W., Reliability-guided phase unwrapping algorithm: A review (2004) Optics and Lasers in Engineering, 42 (3), pp. 245-261Takeda, M., Mutoh, K., Fourier transform profilometry for the automatic measurement of 3-d object shapes (1983) Applied Optics, 22 (24), pp. 3977-3982Villa, J., Araiza, M., Alaniz, D., Ivanov, R., Ortiz, M., Transformation of phase to (x, y, z)-coordinates for the calibration of a fringe projection profilometer (2012) Optics and Lasers in Engineering, 50 (2), pp. 256-261Zhong, J., Weng, J., Dilating gabor transform for the fringe analysis of 3-d shape measurement (2004) Optical Engineering, 43 (4), pp. 895-899Zhong, J., Weng, J., Spatial carrier-fringe pattern analysis by means of wavelet transform: Wavelet transform profilometry (2004) Applied Optics, 43 (26), pp. 4993-4998Zhou, X., Podoleanu, A.G., Yang, Z., Yang, T., Zhao, H., Morphological operation-based bi-dimensional empirical mode decomposition for automatic background removal of fringe patterns (2012) Optics Express, 20 (22), pp. 24247-24262http://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/8976/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/8976oai:repositorio.utb.edu.co:20.500.12585/89762021-02-02 14:49:25.597Repositorio Institucional UTBrepositorioutb@utb.edu.co