Volume 6, Issue 6, December 2013, Pages 1072 - 1081
Benthic Habitat Mapping from Seabed Images using Ensemble of Color, Texture, and Edge Features
- Ashfaqur Rahman
- Corresponding Author
- Ashfaqur Rahman
Available Online 9 January 2017.
- https://doi.org/10.1080/18756891.2013.816055How to use a DOI?
- Benthic habitat mapping, ensemble classifier, image classification
- 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.
- 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 -