Dynamic link matching for multiple object recognition

We present an extended version of dynamic link matching for the recognition of all objects similar to a stored model. With a given complex image containing multiple objects, our system can detect all of those matched with a model regardless of their type of geometric transformation and distortion. This is achieved by allowing simultaneous strengthening of multiple bundles of interlayer links (dynamic links) when local features in the model have more than one counterpart in the image layer. To extract the matched regions, in which dynamic links are established as geometrically invariant mappings, we propose a neural system based on edge dynamics in the edge-mapping parameter space.