A novel hybrid system for shape-based image retrieval using the curvature scale space (CSS) and self-organizing map (SOM) methods is presented. The shape features of images are represented by CSS images extracted from, for example, a large database and they are processed using the PCA technique. These processed CSS images constitutes the training dataset for a SOM neural network which, in turn, will be used for performing efficient image retrieval. Experimental results using a benchmark database are presented to demonstrate the usefulness of the proposed methodology.