Coupled map lattices (CMLs) offer a new framework for modelling visual information processes. The framework involves computing with non-stationary patterns of synchronized activity. In this framework structural features of the visual field emerge through the lateral interaction of locally coupled non-linear maps. Invariant representations develop independent of top-down, or re-entrant, feedback. These representations distort certain features of the pattern, giving rise to visual field illusions. Boundary contours, among others, are emphasized, which suggests that special cases of boundary contour problem could be solved by the system. Simulation studies were performed to test the hypothesis that the system represents visual patterns in a solid/outline invariant manner. A standard back-propagation neural network trained with a CML-filtered set of solid images and tested with CML-filtered outline versions of the same set of images (or vice versa) showed perfect generalization. Generalization failed to occur for unfiltered or contour-filtered images. The CML representations, therefore, were concluded to be solid/outline invariant.