A Texture Analysis Approach to Identifying Sabellaria Spinulosa Colonies in Sidescan Sonar Imagery

Harrison, Richard, Bianconi, Francesco, Harvey, Richard ORCID: https://orcid.org/0000-0001-9925-8316 and Wang, Wenjia (2014) A Texture Analysis Approach to Identifying Sabellaria Spinulosa Colonies in Sidescan Sonar Imagery. In: 2011 Irish Machine Vision and Image Processing Conference. The Institute of Electrical and Electronics Engineers (IEEE), IRL. ISBN 978-1-4673-0230-2

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Offshore wind farms are undergoing unprecedented development as EU member states focus on complying with 2020 renewable energy mandates. However, wind farm site placement requires great care, to avoid compromising protected habitats, such as Sabellaria spinulosa reefs. This paper presents an investigation into the potential of different feature generation methods for identifying sides can sonar image textures characteristic of Sabellaria spinulosa colonies. We propose an extensible test methodology and carry out a detailed comparison of several textural features. Our results show that Gabor filter bank features yield good (up to 89.4% overall) classification accuracies and often outperform other methods in identifying the Sabellaria spinulosa textural class. A Dual-Tree Complex Wavelet Transform, Ring filters and some statistical methods also produce encouraging results.

Item Type: Book Section
Uncontrolled Keywords: texture analysis,sabellaria spinulosa,sonar sidescan,sdg 7 - affordable and clean energy ,/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Data Science and Statistics
Faculty of Science > Research Groups > Smart Emerging Technologies
Depositing User: LivePure Connector
Date Deposited: 14 Sep 2023 16:30
Last Modified: 18 Sep 2023 00:13
URI: https://ueaeprints.uea.ac.uk/id/eprint/93047
DOI: 10.1109/IMVIP.2011.19

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