Neo-cortical sensory areas of the vertebrate brain are organized in terms of topographic maps of peripheral sense-organs. Cortical topography has been generally modeled in terms of a continuous map of a peripheral sensory surface onto a cortical surface. However, the details of cortical architecture do not conform to this concept. Most, if not all, cortical areas consist of an interlaced structure containing multiple topographic maps of distinct classes of neural input. The term ``polymap'' is used to refer to a cortical area which consists of more than one system, interlaced in a globally topographic, but locally columnar fashion. The best known example of a cortical polymap is provided by the ocular dominance column system in layer IV of primate striate cortex, but the puff/extra-puff and orientation systems of surrounding layers also illustrate this concept, as do the thick-thin-interstripe columns of V-2, and the direction columns of MT. Since polymap architecture seems to be a common architectural pattern in the neo-cortex, this work addresses the computational modeling of polymap systems, with the expectation that such modeling will lead to a better understanding of the underlying biology. An algorithm is presented, based on the computational geometry constructs of Generalized Voronoi Polygon and Medial Axis, which provides a general method for simulating polymap systems. It also adds a powerful technique to the repertoire of Digital Image Warping. The algorithm is illustrated using the ocular dominance column and orientation column systems of V-1. In addition, a mechanism is proposed and demonstrated to account for the spatial registration of the ocular dominance and orientation column systems. Computer simulations of the activity evoked by binocular stimuli, as they would appear at the level of layers III and IV in V-1, are shown, and compared to results from recent experiments. Methods of generalizing these techniques to other common polymap cortical areas are outlined.