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Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System

The acquisition of the geometry of general scenes is related to the interplay of surface geometry, material properties and illumination characteristics. Surface texture and non-Lambertian reflectance properties degrade the reconstruction results by structured light technique. Existing structured lig...

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Detalles Bibliográficos
Autores principales: Song, Zhao, Song, Zhan, Ye, Yuping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698391/
https://www.ncbi.nlm.nih.gov/pubmed/33212938
http://dx.doi.org/10.3390/s20226564
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author Song, Zhao
Song, Zhan
Ye, Yuping
author_facet Song, Zhao
Song, Zhan
Ye, Yuping
author_sort Song, Zhao
collection PubMed
description The acquisition of the geometry of general scenes is related to the interplay of surface geometry, material properties and illumination characteristics. Surface texture and non-Lambertian reflectance properties degrade the reconstruction results by structured light technique. Existing structured light techniques focus on different coding strategy and light sources to improve reconstruction accuracy. The hybrid system consisting of a structured light technique and photometric stereo combines the depth value with normal information to refine the reconstruction results. In this paper, we propose a novel hybrid system consisting of stripe-based structured light and photometric stereo. The effect of surface texture and non-Lambertian reflection on stripe detection is first concluded. Contrary to existing fusion strategy, we propose an improved method for stripe detection to reduce the above factor’s effects on accuracy. The reconstruction problem for general scene comes down to using reflectance properties to improve the accuracy of stripe detection. Several objects, including checkerboard, metal-flat plane and free-form objects with complex reflectance properties, were reconstructed to validate our proposed method, which illustrates the effectiveness on improving the reconstruction accuracy of complex objects. The three-step phase-shifting algorithm was implemented and the reconstruction results were given and also compared with ours. In addition, our proposed framework provides a new feasible scheme for solving the ongoing problem of the reconstruction of complex objects with variant reflectance. The problem can be solved by subtracting the non-Lambertian components from the original grey values of stripe to improve the accuracy of stripe detection. In the future, based on stripe structured light technique, more general reflection models can be used to model different types of reflection properties of complex objects.
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spelling pubmed-76983912020-11-29 Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System Song, Zhao Song, Zhan Ye, Yuping Sensors (Basel) Article The acquisition of the geometry of general scenes is related to the interplay of surface geometry, material properties and illumination characteristics. Surface texture and non-Lambertian reflectance properties degrade the reconstruction results by structured light technique. Existing structured light techniques focus on different coding strategy and light sources to improve reconstruction accuracy. The hybrid system consisting of a structured light technique and photometric stereo combines the depth value with normal information to refine the reconstruction results. In this paper, we propose a novel hybrid system consisting of stripe-based structured light and photometric stereo. The effect of surface texture and non-Lambertian reflection on stripe detection is first concluded. Contrary to existing fusion strategy, we propose an improved method for stripe detection to reduce the above factor’s effects on accuracy. The reconstruction problem for general scene comes down to using reflectance properties to improve the accuracy of stripe detection. Several objects, including checkerboard, metal-flat plane and free-form objects with complex reflectance properties, were reconstructed to validate our proposed method, which illustrates the effectiveness on improving the reconstruction accuracy of complex objects. The three-step phase-shifting algorithm was implemented and the reconstruction results were given and also compared with ours. In addition, our proposed framework provides a new feasible scheme for solving the ongoing problem of the reconstruction of complex objects with variant reflectance. The problem can be solved by subtracting the non-Lambertian components from the original grey values of stripe to improve the accuracy of stripe detection. In the future, based on stripe structured light technique, more general reflection models can be used to model different types of reflection properties of complex objects. MDPI 2020-11-17 /pmc/articles/PMC7698391/ /pubmed/33212938 http://dx.doi.org/10.3390/s20226564 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Song, Zhao
Song, Zhan
Ye, Yuping
Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System
title Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System
title_full Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System
title_fullStr Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System
title_full_unstemmed Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System
title_short Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System
title_sort eliminating the effect of reflectance properties on reconstruction in stripe structured light system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698391/
https://www.ncbi.nlm.nih.gov/pubmed/33212938
http://dx.doi.org/10.3390/s20226564
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