We describe a novel system for interaction with large font databases. The system is an efficient tool for browsing in large font databases and as such it can be used by people in the Graphic Arts industry. The proposed approach is based on shape descriptors developed for visual characterization of character images rendered from different fonts. Here the descriptors are used in a visualization of a large font database containing more than 2700 fonts. By applying geometry preserving linear- and non-linear manifold learning methods, in combination with a refinement process, character images of different fonts are organized on a two-dimensional grid, where fonts are positioned based on visual similarity.