Presentation + Paper
27 April 2020 Biosensing across wide areas using LED induced fluorescence
Author Affiliations +
Abstract
A standoff biothreat detection and identification system for scanning large areas was designed, built and tested. The sensor is based on two wavelength ultraviolet light induced fluorescence (UVLIF) measured from a distance. The concept calls for multiple sensor modalities, fused to give the required overall performance. It makes use of multiple cameras, ambient light reflectance, high optical power and wavelength modulated UV LED illumination and synchronized fluorescence detection. A two-step operational mode is described along with results from independent demonstrations for each step. The first step is screening of the scene to recognize the surfaces that maximize the chances of biothreat detection and classification. This step used computer vision and artificial intelligence (semantic segmentation) for automation. The material constituting the surface is identified from color images. A second monochrome camera gives total “fluorescence” images excited with an intensity modulated 368nm UV illuminator. The second demonstration is scanning of slides (the “scene” in this case) from 1.2m away, threat detection (the spots on the slides) and classification via active multispectral fluorescence imaging at two different excitation wavelengths (280 and 368nm) and ambient light reflectance at up to 0.5m2/min. It is primarily the surface characteristics that drive the difficulty of the detection and classification of biological warfare agents (BWAs) on surfaces, along with the amount of BWA present on the surface. This presentation details the results obtained, the lessons learned and the envisioned way ahead.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Francois Babin, Marc Levesque, Louis St-Laurent, Henrique Weber, Simon Turbide, Virginia Foot, and Camilla Robinson "Biosensing across wide areas using LED induced fluorescence", Proc. SPIE 11416, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XXI, 114160H (27 April 2020); https://doi.org/10.1117/12.2560078
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KEYWORDS
Cameras

Light emitting diodes

Image segmentation

Reflectivity

Image processing

Classification systems

Fluorescence spectroscopy

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