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.
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