Classification of Raman Spectra to Detect Hidden Explosives

Document type: Journal Articles
Article type: Original article
Peer reviewed: Yes
Author(s): Naveed R. Butt, Mikael Nilsson, Andreas Jakobsson, Markus Nordberg, Anna Pettersson, Sara Wallin, Henric Östmark
Title: Classification of Raman Spectra to Detect Hidden Explosives
Year: 2011
Volume: 8
Issue: 3
Pagination: 517-521
ISSN: 1545-598X
Publisher: IEEE
ISI number: 000289899000027
Organization: Blekinge Institute of Technology
Department: School of Engineering - Dept. of Electrical Engineering (Sektionen för ingenjörsvetenskap - Avd. för elektroteknik)
School of Engineering S-371 79 Karlskrona
+46 455 38 50 00
Authors e-mail:
Language: English
Abstract: Raman spectroscopy is a laser-based vibrational technique that can provide spectral signatures unique to a multitude of compounds. The technique is gaining widespread interest as a method for detecting hidden explosives due to its sensitivity and ease of use. In this letter, we present a computationally efficient classification scheme for accurate standoff identification of several common explosives using visible-range Raman spectroscopy. Using real measurements, we evaluate and modify a recent correlation-based approach to classify Raman spectra from various harmful and commonplace substances. The results show that the proposed approach can, at a distance of 30 m, or more, successfully classify measured Raman spectra from several explosive substances, including nitromethane, trinitrotoluene, dinitrotoluene, hydrogen peroxide, triacetone triperoxide, and ammonium nitrate.
Subject: Signal Processing\Detection and Classification
Signal processing\Image and Video Processing