Spectral pattern recognition of controlled substances in street samples using artificial neural network system

Larisa Poryvkina; Valeri Aleksejev; Sergey M. Babichenko; Tatjana Ivkina

doi:10.1117/12.883408

26 April 2011 Spectral pattern recognition of controlled substances in street samples using artificial neural network system

Larisa Poryvkina, Valeri Aleksejev, Sergey M. Babichenko, Tatjana Ivkina

Author Affiliations +

Proceedings Volume 8055, Optical Pattern Recognition XXII; 80550R (2011) https://doi.org/10.1117/12.883408
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

The NarTest fluorescent technique is aimed at the detection of analyte of interest in street samples by recognition of its specific spectral patterns in 3-dimentional Spectral Fluorescent Signatures (SFS) measured with NTX2000 analyzer without chromatographic or other separation of controlled substances from a mixture with cutting agents. The illicit drugs have their own characteristic SFS features which can be used for detection and identification of narcotics, however typical street sample consists of a mixture with cutting agents: adulterants and diluents. Many of them interfere the spectral shape of SFS. The expert system based on Artificial Neural Networks (ANNs) has been developed and applied for such pattern recognition in SFS of street samples of illicit drugs.

Citation Download Citation

Larisa Poryvkina, Valeri Aleksejev, Sergey M. Babichenko, and Tatjana Ivkina "Spectral pattern recognition of controlled substances in street samples using artificial neural network system", Proc. SPIE 8055, Optical Pattern Recognition XXII, 80550R (26 April 2011); https://doi.org/10.1117/12.883408

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