We are using active infrared (IR) spectroscopic imaging to detect trace explosives on surfaces at proximal distances up to a few meters. The technology comprises an IR quantum cascade laser (QCL) for illumination and an IR focal plane array (FPA) sensor to collect signal backscattered from surfaces of interest. By sweeping the wavelength of the QCL while collecting image frames with the FPA, we generate an active hyperspectral image (HSI) cube. The HSI cube contains both spatial and spectral information, where the spectrum of a pixel, or region of interest within the image, can be extracted and compared against a known threat library. These cubes are fed into a convolutional neural network (CNN) trained on purely synthetic data to identify chemicals in the field of view. The CNN identifies chemicals by their IR signature and identifies their location within the image.
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