An automatic detection software for differential reflection spectroscopy

Recent terrorist attacks have sprung a need for a large scale explosive detector. Our group has developed differential reflection spectroscopy which can detect explosive residue on surfaces such as parcel, cargo and luggage. In short, broad band ultra-violet and visible light is shone onto a material (such as a parcel) moving on a conveyor belt. Upon reflection off the surface, the light intensity is recorded with a spectrograph (spectrometer in combination with a CCD camera). This reflected light intensity is then subtracted and normalized with the next data point collected, resulting in differential reflection spectra in the 200-500 nm range. Explosives show spectral finger-prints at specific wavelengths, for example, the spectrum of 2,4,6, trinitrotoluene (TNT) shows an absorption edge at 420 nm. Additionally, we have developed an automated software which detects the characteristic features of explosives. One of the biggest challenges for the algorithm is to reach a practical limit of detection. In this study, we introduce our automatic detection software which is a combination of principal component analysis and support vector machines. Finally we present the sensitivity and selectivity response of our algorithm as a function of the amount of explosive detected on a given surface.