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.
A Texture Analysis Approach to Identifying Sabellaria Spinulosa Colonies in Sidescan Sonar Imagery
BIANCONI, Francesco;
2011
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
