Benthic Habitat Mapping from Seabed Images using Ensemble of Color, Texture, and Edge Features

DOI

10.1080/18756891.2013.816055How to use a DOI?

Keywords

Benthic habitat mapping, ensemble classifier, image classification

Abstract

In this paper we present a novel approach to produce benthic habitat maps from sea floor images in Derwent estuary. We have developed a step–by–step segmentation method to separate sea–grass, sand, and rock from the sea floor image. The sea–grass was separated first using color filtering. The remaining image was classified into rock and sand based on color, texture, and edge features. The features were fed into an ensemble classifier to produce better classification results. The base classifiers in the ensemble were made complementary by changing the weight (i.e. cost of misclassification) of the classes. The habitat maps were produced for three regions in Derwent estuary. Experimental results demonstrate that the proposed method can indentify different objects and produce habitat maps from the sea–floor images with very high accuracy.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - JOUR
AU  - Ashfaqur Rahman
PY  - 2013
DA  - 2013/11/01
TI  - Benthic Habitat Mapping from Seabed Images using Ensemble of Color, Texture, and Edge Features
JO  - International Journal of Computational Intelligence Systems
SP  - 1072
EP  - 1081
VL  - 6
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.816055
DO  - 10.1080/18756891.2013.816055
ID  - Rahman2013
ER  -