International Journal of Computational Intelligence Systems

Volume 6, Issue 6, December 2013, Pages 1072 - 1081

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

Authors
Ashfaqur Rahman
Corresponding Author
Ashfaqur Rahman
Available Online 9 January 2017.
DOI
https://doi.org/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.
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This is an open access article distributed under the CC BY-NC license.

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
6 - 6
Pages
1072 - 1081
Publication Date
2017/01
ISSN
1875-6883
DOI
https://doi.org/10.1080/18756891.2013.816055How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Ashfaqur Rahman
PY  - 2017
DA  - 2017/01
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  - https://doi.org/10.1080/18756891.2013.816055
ID  - Rahman2017
ER  -