Modelling active contours using neural networks isomorphic to boundaries

We propose a new technique, based on self-organization, for localizing salient contours in an image, with applications to, for instance, object and character recognition, stereopsis and motion tracking. A neuronal network which is isomorphic to the template/initial contour is created. This network acts as an active contour, which, using self-organization, undergoes deformation in an attempt to cling on to the nearest salient contour in the test image. The application areas of the model proposed are similar to "snake", but distinct from it both in the underlying mathematics and implementation. The new technique is illustrated with some examples.