Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging

The identification of hazardous chemicals based on hyperspectral imaging is an important emergent means for the prevention of explosion accidents and the early warning of secondary hazards. In this study, we used a combination of spectral curve matching based on full-waveform characteristics and spe...

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Main Authors: Yanlong Sun, Xinming Qian, Yangyang Liu, Jianwei Wang, Qunbo Lv, Mengqi Yuan
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/13/2608
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spelling doaj-ce81f1f67f364e2abfa706855299eb9d2021-07-15T15:44:39ZengMDPI AGRemote Sensing2072-42922021-07-01132608260810.3390/rs13132608Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral ImagingYanlong Sun0Xinming Qian1Yangyang Liu2Jianwei Wang3Qunbo Lv4Mengqi Yuan5State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaState Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, ChinaThe identification of hazardous chemicals based on hyperspectral imaging is an important emergent means for the prevention of explosion accidents and the early warning of secondary hazards. In this study, we used a combination of spectral curve matching based on full-waveform characteristics and spectral matching based on spectral characteristics to identify the hazardous chemicals, and proposed a method to quantitatively characterize the matching degree of the spectral curves of hazardous chemicals. The results showed that the four hazardous chemicals, sulfur, red phosphorus, potassium permanganate, and corn starch had bright colors, distinct spectral curve characteristics, and obvious changes in reflectivity, which were easy to identify. Moreover, the matching degree of their spectral curves was positively correlated with their reflectivity. However, the spectral characteristics of carbon powder, strontium nitrate, wheat starch, and magnesium–aluminum alloy powder were not obvious, with no obvious characteristic peaks or trends of change in reflectivity. Except for the reflectivity and the matching degree of the carbon powder being maintained at a low level, the reflectivity of the remaining three samples was relatively close, so that it was difficult to identify with the spectral curves alone, and color information should be considered for further identification.https://www.mdpi.com/2072-4292/13/13/2608hazardous chemicalshyperspectral imagingimage identification
collection DOAJ
language English
format Article
sources DOAJ
author Yanlong Sun
Xinming Qian
Yangyang Liu
Jianwei Wang
Qunbo Lv
Mengqi Yuan
spellingShingle Yanlong Sun
Xinming Qian
Yangyang Liu
Jianwei Wang
Qunbo Lv
Mengqi Yuan
Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging
Remote Sensing
hazardous chemicals
hyperspectral imaging
image identification
author_facet Yanlong Sun
Xinming Qian
Yangyang Liu
Jianwei Wang
Qunbo Lv
Mengqi Yuan
author_sort Yanlong Sun
title Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging
title_short Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging
title_full Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging
title_fullStr Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging
title_full_unstemmed Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging
title_sort identification of typical solid hazardous chemicals based on hyperspectral imaging
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-07-01
description The identification of hazardous chemicals based on hyperspectral imaging is an important emergent means for the prevention of explosion accidents and the early warning of secondary hazards. In this study, we used a combination of spectral curve matching based on full-waveform characteristics and spectral matching based on spectral characteristics to identify the hazardous chemicals, and proposed a method to quantitatively characterize the matching degree of the spectral curves of hazardous chemicals. The results showed that the four hazardous chemicals, sulfur, red phosphorus, potassium permanganate, and corn starch had bright colors, distinct spectral curve characteristics, and obvious changes in reflectivity, which were easy to identify. Moreover, the matching degree of their spectral curves was positively correlated with their reflectivity. However, the spectral characteristics of carbon powder, strontium nitrate, wheat starch, and magnesium–aluminum alloy powder were not obvious, with no obvious characteristic peaks or trends of change in reflectivity. Except for the reflectivity and the matching degree of the carbon powder being maintained at a low level, the reflectivity of the remaining three samples was relatively close, so that it was difficult to identify with the spectral curves alone, and color information should be considered for further identification.
topic hazardous chemicals
hyperspectral imaging
image identification
url https://www.mdpi.com/2072-4292/13/13/2608
work_keys_str_mv AT yanlongsun identificationoftypicalsolidhazardouschemicalsbasedonhyperspectralimaging
AT xinmingqian identificationoftypicalsolidhazardouschemicalsbasedonhyperspectralimaging
AT yangyangliu identificationoftypicalsolidhazardouschemicalsbasedonhyperspectralimaging
AT jianweiwang identificationoftypicalsolidhazardouschemicalsbasedonhyperspectralimaging
AT qunbolv identificationoftypicalsolidhazardouschemicalsbasedonhyperspectralimaging
AT mengqiyuan identificationoftypicalsolidhazardouschemicalsbasedonhyperspectralimaging
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