Identifying distinguishing size and shape features of mine-like objects in sidescan sonar imagery

The purpose of this work is to identify features that can successfully classify objects that appear in sidescan sonar imagery as belonging to one of 3 mine classes or a non-mines class. Naval mine hunters identify mines in the imagery primarily using the size and shape of signature bright and dark regions, referred to as the highlight and shadow respectively. A data set of real sidescan sonar imagery was provided by Defence Research and Development Canada. Many feature sets, some novel, were tested for their ability to discriminate between mines and non-mines, as well as between the different types of mines (cylinder, truncated cone, and sphere) and the non-mines. Classification was performed using a linear discriminant function. Ultimately, several good features representing certain size and shape qualities were identified. These include measures of object height, shadow elongation, shadow 2-rotational symmetry, and particular shadow shapes (using Fourier descriptors).