Research Scholar, Department of Bio-Technology, AMET University, Chennai
Marine ecosystem has changes in indicators like marine phytoplanktons are unicellular algae with avariety of shapes and decoration. Phytoplankton recognition used aK-Nearest Neighbor (KNN)classifier and dual layer in this study. After that classification phase, here this method used a K-NN mechanism from texture information such as moment, geometricand gray level co-occurrence matrix features and shapes also used. Each individualclassifier has its own specific input feature and decisionmechanism. The marine phytoplankton recognition experimentshows that the proposed classification method outperforms twowell-known stand-alone classifiers, K-NN.
Marine Phytoplankton Recognition, Moments, K-Nnclassification
