Classification of seafloor habitats using Genetic Programming

Abstract

In this paper we use Genetic Programming for the classification of different seafloor habitats, based on the acoustic backscatter data from an echo sounder. By dividing the multiple-class problem into several two-class problems, we were able to produce nearly perfect results, providing total discrimination between most of the seafloor types used in this study. We discuss the quality of these results and provide ideas to further improve the classification performance. © 2008 Springer-Verlag Berlin Heidelberg.