Open AccessIdentification method of EDXRD spectra for illicit substance detection
Author(s) -
Qinghua Song,
Yifan Chen,
Xin Wang,
Baolu Yang,
Jie Xu,
Kai Xiong,
Baozhong Mu
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.026163
Subject(s) - principal component analysis , identification (biology) , diffraction , explosive material , computer science , linear discriminant analysis , multispectral image , energy (signal processing) , optics , spectral line , pattern recognition (psychology) , materials science , artificial intelligence , physics , statistics , mathematics , chemistry , botany , organic chemistry , astronomy , biology
The energy-dispersive X-ray diffraction technique can be more practical and accurate for security applications such as detecting drugs and explosives. Here, an accurate multivariate discriminant analysis (MDA) method is used to identify the energy-dispersive X-ray diffraction spectra of illicit contraband. MDA is a comprehensive algorithm based on the principal component analysis algorithm, spectral angle matching method, and correlation coefficient method. Experiments are performed to acquire the diffracted spectra of drugs and common daily necessities. The accurate identification of models for an unknown substance can indicate the substance type in an already established database. Even in the case of shielding, the concealed object can be correctly identified, and the identification accuracy improved much compared with other algorithms.