Invariant descriptors of sonar textures from spatial statistics of local features

This paper addresses the development of invariant descriptors for sonar texture based on spatial statistics of local features. We suggest using a hierarchical clustering algorithm to construct a set of codebook from the vector descriptor of keypoints. Spatial point process model allows us to estimate a co-occurrence statistics of the marks of neighboring keypoints in various study region. The resulting descriptor is applied to texture classification using a discriminative method (K-NN or SVM). Experiments were carried out on a set of real sidescan sonar images aiming to compare our proposed descriptor with other texture descriptors.