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A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System

Hyperspectral and three-dimensional measurements can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. The combination of these two kinds of data can provide new insights into objects, which has gained attention in the fields of agricu...

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Detalles Bibliográficos
Autores principales: Zhao, Huijie, Xu, Lunbao, Shi, Shaoguang, Jiang, Hongzhi, Chen, Da
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948655/
https://www.ncbi.nlm.nih.gov/pubmed/29614839
http://dx.doi.org/10.3390/s18041068
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author Zhao, Huijie
Xu, Lunbao
Shi, Shaoguang
Jiang, Hongzhi
Chen, Da
author_facet Zhao, Huijie
Xu, Lunbao
Shi, Shaoguang
Jiang, Hongzhi
Chen, Da
author_sort Zhao, Huijie
collection PubMed
description Hyperspectral and three-dimensional measurements can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. The combination of these two kinds of data can provide new insights into objects, which has gained attention in the fields of agricultural management, plant phenotyping, cultural heritage conservation, and food production. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. In addition, using slit-based spectrometers and point-based 3D sensors extends the working hours in farms due to the narrow field of view (FOV). Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information. Furthermore, fiber-reformatting imaging spectrometry (FRIS) is adopted to acquire the hyperspectral images. Test experiments are conducted for the verification of the system accuracy, and vegetation measurements are carried out to demonstrate its feasibility. The proposed system is an improvement in multiple data acquisition and has the potential to improve plant phenotyping.
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spelling pubmed-59486552018-05-17 A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System Zhao, Huijie Xu, Lunbao Shi, Shaoguang Jiang, Hongzhi Chen, Da Sensors (Basel) Article Hyperspectral and three-dimensional measurements can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. The combination of these two kinds of data can provide new insights into objects, which has gained attention in the fields of agricultural management, plant phenotyping, cultural heritage conservation, and food production. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. In addition, using slit-based spectrometers and point-based 3D sensors extends the working hours in farms due to the narrow field of view (FOV). Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information. Furthermore, fiber-reformatting imaging spectrometry (FRIS) is adopted to acquire the hyperspectral images. Test experiments are conducted for the verification of the system accuracy, and vegetation measurements are carried out to demonstrate its feasibility. The proposed system is an improvement in multiple data acquisition and has the potential to improve plant phenotyping. MDPI 2018-04-02 /pmc/articles/PMC5948655/ /pubmed/29614839 http://dx.doi.org/10.3390/s18041068 Text en © 2018 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
Zhao, Huijie
Xu, Lunbao
Shi, Shaoguang
Jiang, Hongzhi
Chen, Da
A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System
title A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System
title_full A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System
title_fullStr A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System
title_full_unstemmed A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System
title_short A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System
title_sort high throughput integrated hyperspectral imaging and 3d measurement system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948655/
https://www.ncbi.nlm.nih.gov/pubmed/29614839
http://dx.doi.org/10.3390/s18041068
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