Abstract In image database systems, we often want to retrieve images whose contents satisfy certain conditions specified in an iconic query (i.e. queries that involve input images and conditions on them). One type of image data retrieval called ‘shape similarity-based retrieval” involves retrieval of images containing one or more shapes similar to the shapes specified in the query or shapes present in the query image. In this paper, a new approach to shape similarity-based retrieval is proposed. The proposed approach is flexible enough to handle query images with overlapping or touching parts. In this approach a shape is represented by a set of boundary components, called features. Each structural feature is encoded as a point in multidimensional space. A similar or identical structural component (or shape) can be found by organizing the data in any multidimensional point access index structure. A prototype system is described in detail. Some experimental results are also presented to demonstrate the performance of the proposed technique.