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16 April 2008 Optical recognition of biological agents
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Differentiation between particulate biological agents and non-biological agents is typically performed via a time-consuming "wet chemistry" process or through the use of fluorescent and spectroscopic analysis. However, while these methods can provide definitive recognition of biological agents, many of them have to be performed in a laboratory environment, or are difficult to implement in the field. Optical recognition techniques offer an additional recognition approach that can provide rapid analysis of a material in-situ to identify those materials that may be biological in nature. One possible application is to use these techniques to "screen" suspicious materials and to identify those that are potentially biological in nature. Suspicious materials identified by this screening process can then be analyzed in greater detail using the other, more definitive (but time consuming) analysis techniques. This presentation will describe the results of a feasibility study to determine whether optical pattern recognition techniques can be used to differentiate biological related materials from non-biological materials. As part of this study, feature extraction algorithms were developed utilizing multiple contrast and texture based features to characterize the macroscopic properties of different materials. In addition, several pattern recognition approaches using these features were tested including cluster analysis and neural networks. Test materials included biological agent simulants, biological agent related materials, and non-biological materials (suspicious white powders). Results of a series of feasibility tests will be presented along with a discussion of the potential field applications for these techniques.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chris W. Baumgart, Kim Dalton Linder, and Josh J. Trujillo "Optical recognition of biological agents", Proc. SPIE 6969, Signal and Data Processing of Small Targets 2008, 696909 (16 April 2008);

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