A novel one shot object profilometry system using Direct Sequence Spread Spectrum profilometry

Woolford, S; Burnett, IS

A novel one shot object profilometry system using Direct Sequence Spread Spectrum profilometry

Woolford, S Burnett, IS

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Publication Type:: Conference Proceeding
Citation:: 2013 IEEE 11th IVMSP Workshop: 3D Image/Video Technologies and Applications, IVMSP 2013 - Proceedings, 2013
Issue Date:: 2013-11-28

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Field	Value	Language
dc.contributor.author	Woolford, S	en_US
dc.contributor.author	Burnett, IS https://orcid.org/0000-0003-3795-7722	en_US
dc.date.issued	2013-11-28	en_US
dc.identifier.citation	2013 IEEE 11th IVMSP Workshop: 3D Image/Video Technologies and Applications, IVMSP 2013 - Proceedings, 2013	en_US
dc.identifier.isbn	9781467358583	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120694
dc.description.abstract	In this paper a new method of determining 3D object shape using patterns derived from Direct Sequence Spread Spectrum (DSSS) and an Unscented Kalman Filter (UKF) is presented. First a binary message is encoded via Binary Phase Shift Keying (BPSK), and spread using pseudo-random spreading to create a pattern. An Iterative Unscented Kalman Filter (IUKF) is then used to determine the deformation in the pattern due to an object, and a Kalman smoother is used to reduce noise in the deformation estimation. Results show that the iterative UKF is able to determine the deformation in the pattern with a lower absolute error residual between the ground truth and estimated deformation than the non-iterated UKF. Results of the accompanying Cramer-Rao lower bounds show that the lower bound on the DSSS Pattern is lower than that of the fringe pattern. © 2013 IEEE.	en_US
dc.relation.ispartof	2013 IEEE 11th IVMSP Workshop: 3D Image/Video Technologies and Applications, IVMSP 2013 - Proceedings	en_US
dc.relation.isbasedon	10.1109/IVMSPW.2013.6611896	en_US
dc.title	A novel one shot object profilometry system using Direct Sequence Spread Spectrum profilometry	en_US
dc.type	Conference Proceeding
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

In this paper a new method of determining 3D object shape using patterns derived from Direct Sequence Spread Spectrum (DSSS) and an Unscented Kalman Filter (UKF) is presented. First a binary message is encoded via Binary Phase Shift Keying (BPSK), and spread using pseudo-random spreading to create a pattern. An Iterative Unscented Kalman Filter (IUKF) is then used to determine the deformation in the pattern due to an object, and a Kalman smoother is used to reduce noise in the deformation estimation. Results show that the iterative UKF is able to determine the deformation in the pattern with a lower absolute error residual between the ground truth and estimated deformation than the non-iterated UKF. Results of the accompanying Cramer-Rao lower bounds show that the lower bound on the DSSS Pattern is lower than that of the fringe pattern. © 2013 IEEE.

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http://hdl.handle.net/10453/120694