Automated object recognition of blue-green algae for measuring water quality—A preliminary study

In this paper a computer algorithm for the automated detection of blue-green algae is presented. Samples of seven species of blue-green algae and two species of green algae were examined under a microscope and transferred to a computer. The microscope pictures were stored as digital images. In order to locate the organisms Image Segmentation routines were applied. Image Enhancement improved the quality and appearance of the species in the images. With the aid of shape algorithms (Fourier Descriptors, Moment Invariants) and textural algorithms (Cell finding algorithm, Statistical measures) certain features were identified, extracted and then fed into a classifier. The classifier, using Discriminant Analysis, was then able to predict 155 out of 158 samples correctly.