Identification of phytoplankton species using Hermite transform

We apply a Hermite transform joint with a classical correlation analysis to successfully recognize phytoplankton species even in such complicated cases when the relevant images reveal the patterns of inhomogeneous illumination and natural distortions. The images of phytoplankton species are divided into two groups consisting of 30 samples each. Those belonging to the first group are the images with neither inhomogeneous illumination nor noise, while the second one embraces the images with the background noise, inhomogeneous illumination and real distortions. We find the optimal Hermite-transform order to be used in finding correlations among the images. It is given by a so-called ‘peak correlation energy’ metric. Using the images modified by the Hermite transform with a classical Vander-Lugt filter, we are able to distinguish all the phytoplankton species in the test images. A classical composite filter is also applied to the two groups of images. For the first group, the composite filter is created using different patterns of illumination of the same species. In the second group, this filter is composed using various specimens of the same species in order to identify a specific species. In the both cases, the Hermite transform joined with the classical correlation analysis can distinguish all the phytoplankton species.

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