Material Sensing with Spatial and Spectral Resolution Based on an Integrated Near-Infrared Spectral Sensor and a CMOS Camera

Measuring the composition of materials at a distance is a key requirement in industrial process monitoring, recycling, precision agriculture, and environmental monitoring. Spectral imaging in the visible or near-infrared (NIR) spectral bands provides a potential solution by combining spatial and spectral information, and its application has seen significant growth over recent decades. Low-cost solutions for visible multispectral imaging (MSI) have been developed due to the widespread availability of silicon detectors, which are sensitive in this spectral region. In contrast, development in the NIR has been slower, primarily due to the high cost of indium gallium arsenide (InGaAs) detector arrays required for imaging. This work aims to bridge this gap by introducing a standoff material sensing concept which combines spatial and spectral resolution without the hardware requirements of traditional spectral imaging systems. It combines spatial imaging in the visible range with a CMOS camera and NIR spectral measurement at selected points of the scene using an NIR spectral sensor. This allows the chemical characterization of different objects of interest in a scene without acquiring a full spectral image. We showcase its application in plastic classification, a key functionality in sorting and recycling systems. The system demonstrated the capability to classify visually identical plastics of different types in a standoff measurement configuration and to produce spectral measurements at up to 100 points in a scene.

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Publication Details

Journal
Sensors
Published
2025-05-23
DOI
https://doi.org/10.3390/s25113295
Citations
1
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
0.67

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article

Material Sensing with Spatial and Spectral Resolution Based on an Integrated Near-Infrared Spectral Sensor and a CMOS Camera

Don M. J. van Elst, René P. J. van Veldhoven, Anne van Klinken, B. Delaney et al.
1 citations
Sensors
Advanced Chemical Sensor Technologies
0.67
article

Material Sensing with Spatial and Spectral Resolution Based on an Integrated Near-Infrared Spectral Sensor and a CMOS Camera

Don M. J. van Elst, René P. J. van Veldhoven, Anne van Klinken, B. Delaney, Andrea Fiore, S. Buntinx
article en
1 citations

Abstract

Measuring the composition of materials at a distance is a key requirement in industrial process monitoring, recycling, precision agriculture, and environmental monitoring. Spectral imaging in the visible or near-infrared (NIR) spectral bands provides a potential solution by combining spatial and spectral information, and its application has seen significant growth over recent decades. Low-cost solutions for visible multispectral imaging (MSI) have been developed due to the widespread availability of silicon detectors, which are sensitive in this spectral region. In contrast, development in the NIR has been slower, primarily due to the high cost of indium gallium arsenide (InGaAs) detector arrays required for imaging. This work aims to bridge this gap by introducing a standoff material sensing concept which combines spatial and spectral resolution without the hardware requirements of traditional spectral imaging systems. It combines spatial imaging in the visible range with a CMOS camera and NIR spectral measurement at selected points of the scene using an NIR spectral sensor. This allows the chemical characterization of different objects of interest in a scene without acquiring a full spectral image. We showcase its application in plastic classification, a key functionality in sorting and recycling systems. The system demonstrated the capability to classify visually identical plastics of different types in a standoff measurement configuration and to produce spectral measurements at up to 100 points in a scene.

SensorsVol. 25(11)
Eindhoven University of Technology (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 31%
Advanced Chemical Sensor Technologies
0.67
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