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Statistical signal modeling techniques for automated recognition of water-borne microbial shapes

The purpose of this paper is to present some preliminary results related to the problem of automated detection and identification of water-borne microbiota (bacteria, algae, and protozoa). The topics addressed include acquisition and creation of a microbiota image database, enhancement using Wiener/nonlinear filters, statistical modeling of shape contours, and classification.