Pictures of phytoplankton samples were analyzed as raster images by means of a television camera and a Robotron 4200 computer. A feature vector described the objects irrespective of their angle. Each of the five genera involved were identifiable by a characteristic point cluster in a p-dimensional feature space. A learning method was used during development of the classification structure, and the quality of identification was increased incrementally to the greatest possible degree.Asterionelb forrnosa was identified in all cases without error despite the relatively coarse scanning grid. Errors in the identification of Fragilaria crotonensis can be reduced by improving the resolution (over 100 picture elements per colony).
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