In this paper, we introduce several methods for symmetry detection and present results of their experimental evaluation on diatom images. The methods are based on distance lists, cyclic string matching, and graylevel gradient direction histogram. From the experimental results, it can be concluded that symmetry information is useful for various indexing tasks in image databases. Types of symmetry considered in this paper are rotational and reflectional symmetry of the shape as well as symmetry of the graylevel distribution of the internal structure of objects. Using a symmetry based indexing scheme as proposed in this paper, the effort for the subsequent task of diatom classification can significantly be reduced.