ABSTRACT. In this paper we introduce some new techniques for modeling fractal images using concepts from the theory of iterated function systems and morphological skeletons. In the theory of iterated function systems, a fractal image can be modeled arbitrarily closely as the attractor of a finite set of affine maps. We use the morphological skeleton to provide us with sufficient information about the parameters of these affine maps. This technique has applications for fractal synthesis, computer graphics, and coding. Images that exhibit self-similarity, such as leaves, trees, mountains, and clouds, can be easily modeled using these techniques. Slight perturbations in the parameters of the model create variations in the image that can be used in animation. Finally, the small number of parameters in the model allows for very efficient image compression.