Article ; Online: Stand-off Hyperspectral Raman Imaging and Random Decision Forest Classification: A Potent Duo for the Fast, Remote Identification of Explosives.
2019 Volume 91, Issue 12, Page(s) 7712–7718
Abstract: In this study, we present a stand-off hyperspectral Raman imager (HSRI) for the fast detection and classification of different explosives at a distance of 15 m. The hyperspectral image cube is created by using a liquid crystal tunable filter (LCTF) to ... ...
| Abstract | In this study, we present a stand-off hyperspectral Raman imager (HSRI) for the fast detection and classification of different explosives at a distance of 15 m. The hyperspectral image cube is created by using a liquid crystal tunable filter (LCTF) to select a specific Raman shift and sequentially imaging spectral images onto an intensified CCD camera. The laser beam is expanded to illuminate the field of view of the HSRI and thereby improves large area scanning of suspicious surfaces. The collected hyperspectral image cube (HSI) is evaluated and classified using a random decision forest (RDF) algorithm. The RDF is trained with a training set of mg-amounts of different explosives, i.e., TNT, RDX, PETN, NaClO |
|---|---|
| Language | English |
| Publishing date | 2019-06-05 |
| Publishing country | United States |
| Document type | Journal Article ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 1508-8 |
| ISSN | 1520-6882 ; 0003-2700 |
| ISSN (online) | 1520-6882 |
| ISSN | 0003-2700 |
| DOI | 10.1021/acs.analchem.9b00890 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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