The recognition of aquatic organisms plays a crucial role in the monitoring of the pollution and for the adoption of rapid preventive actions. A compact microscopic optical imaging system is proposed in order to acquire and treat the multibands fluorescence of several pigments in phytoplankton organisms. Two algorithms for automatic recognition of phytoplankton were proposed with a minimum number of calibration parameters. The first algorithm provides a morphological recognition based on "watershed" segmentation and Fourier descriptors, while the second one builds fluorescence pigment images by "k-means" partition of intensity ratios. The operation of these algorithms was illustrated by the study of two different organisms: a cyanobacteria (Dolichospermum sp.) and an alga (Cladophora sp.). The family and the genus of these organisms were then classified into a database which is independent of the size, the orientation and the position of the specimens in the images.
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