Visual clustering of trademarks using the self-organizing map

Abstract

This paper describes the experiments used to investigate ways in which digitised trademark images can be visually clustered on a 2-D surface, using the topological properties of the self-organizing map. Experiments were carried out on a set of original and edge detected binary trademark images, as well as their moment invariants, angular radial transformations and wavelet feature vectors. A radial based precision-recall measure was also used to evaluate the results objectively. Initial results are encouraging.