Signal processing of Raman signatures and realtime identification of hazardous molecules using continuous wavelet transformation (CWT)

Continuous use of explosives by terrorists throughout the world has led to the great necessity in explosives detection technology, especially in technologies that have potential for stand-off detection. The Raman vibrational spectrum of molecules provides an excellent fingerprint for species identification. Analysis of Raman signatures manually is time-consuming and cannot be afford by security personal in real scenario.

Automation of detection, acquisition and analysis of Raman signal is required for operations in real scenario. In this work, we have developed software which caters all these process automatically and finally mentions name of material under observation for standoff detection. This is based on continuous wavelet transformation (CWT). This algorithm/ software is capable of identifications/ discrimination of very similar chemicals like trinitrobenzene (TNB), trinitrotoluene (TNT) and dinitrotoluene (DNT).