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This correspondence examines the classification potential of two techniques based on spiral sampling of binary images of zooplankton. Image pixels are rearranged into a one-dimensional sequence by selecting samples in a spiral manner starting from the edge of the image and proceeding toward the center. The properties of this sample sequence are examined by Fourier transform and correlation techniques, using images from six major zooplankton categories of varying orientation and size. The ability of features extracted from spiral sequences to classify zooplankton samples, and their classification accuracy are investigated.