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

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.