High-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications

Conventional imaging practices used for the inspection and monitoring of biological specimens employ RGB cameras with limited capabilities for early identification of diseases or abnormalities. In this work, we demonstrate and validate a quick, non-destructive, and precise inspection method utilizin...

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Main Authors: Antony, Maria Merin, Suchand Sandeep, Chandramathi Sukumaran, Lim, Hoong-Ta, Matham, Murukeshan Vadakke
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/173207
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1732072024-01-24T08:21:58Z High-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications Antony, Maria Merin Suchand Sandeep, Chandramathi Sukumaran Lim, Hoong-Ta Matham, Murukeshan Vadakke School of Mechanical and Aerospace Engineering Centre for Optical and Laser Engineering Science::Physics::Optics and light Hyperspectral Imaging Spectral Mapping Conventional imaging practices used for the inspection and monitoring of biological specimens employ RGB cameras with limited capabilities for early identification of diseases or abnormalities. In this work, we demonstrate and validate a quick, non-destructive, and precise inspection method utilizing an in-house developed push broom ultra-spectral imager. Precise image classification based on ultra-spectral signatures can provide fully automated machine vision capabilities, reducing inspection time, human errors, and man-hours. The proposed method has high spectral resolution (Δλ < 1 nm) with 756 spectral bands, improved detection sensitivity, and high spatial resolution, which could potentially enable early-stage detection and accurate classification of abnormalities or diseases. Two potential applications of the developed system in agriculture and biomedical fields are demonstrated. Economic Development Board (EDB) National Research Foundation (NRF) Singapore Food Agency Published version This research is supported by the National Research Foundation, Singapore and Singapore Food Agency, under its Singapore Food Story R&D Programme (Theme 1: Sustainable Urban Food Production) Grant Call (SFS_RND_SUFP_001_03). The authors also acknowledge financial support received through COLEEDB funding at COLE, NTU. 2024-01-17T05:22:40Z 2024-01-17T05:22:40Z 2023 Journal Article Antony, M. M., Sandeep, C. S. S., Lim, H. & Matham, M. V. (2023). High-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications. Journal of Biomedical Photonics and Engineering, 9(3), 030304-. https://dx.doi.org/10.18287/JBPE23.09.030304 2411-2844 https://hdl.handle.net/10356/173207 10.18287/JBPE23.09.030304 2-s2.0-85174935870 3 9 030304 en SFS_RND_SUFP_001_03 Journal of Biomedical Photonics and Engineering © 2023 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Physics::Optics and light
Hyperspectral Imaging
Spectral Mapping
spellingShingle Science::Physics::Optics and light
Hyperspectral Imaging
Spectral Mapping
Antony, Maria Merin
Suchand Sandeep, Chandramathi Sukumaran
Lim, Hoong-Ta
Matham, Murukeshan Vadakke
High-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications
description Conventional imaging practices used for the inspection and monitoring of biological specimens employ RGB cameras with limited capabilities for early identification of diseases or abnormalities. In this work, we demonstrate and validate a quick, non-destructive, and precise inspection method utilizing an in-house developed push broom ultra-spectral imager. Precise image classification based on ultra-spectral signatures can provide fully automated machine vision capabilities, reducing inspection time, human errors, and man-hours. The proposed method has high spectral resolution (Δλ < 1 nm) with 756 spectral bands, improved detection sensitivity, and high spatial resolution, which could potentially enable early-stage detection and accurate classification of abnormalities or diseases. Two potential applications of the developed system in agriculture and biomedical fields are demonstrated.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Antony, Maria Merin
Suchand Sandeep, Chandramathi Sukumaran
Lim, Hoong-Ta
Matham, Murukeshan Vadakke
format Article
author Antony, Maria Merin
Suchand Sandeep, Chandramathi Sukumaran
Lim, Hoong-Ta
Matham, Murukeshan Vadakke
author_sort Antony, Maria Merin
title High-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications
title_short High-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications
title_full High-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications
title_fullStr High-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications
title_full_unstemmed High-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications
title_sort high-resolution ultra-spectral imager for advanced imaging in agriculture and biomedical applications
publishDate 2024
url https://hdl.handle.net/10356/173207
_version_ 1789482958515601408