Analytic fusion of edge maps

An analytic method for the fusion of range and intensity edge maps is proposed for applications in robotic vision and sensing. This method addresses the integration of registered information to increase one´s confidence about the presence/absence of a feature (edge) in a depicted scene. The algorithm is based on the interaction between the following two constraints: the principle of token corroboration, which tends to maximize the value of the output edge map at a given location if one input edge map features an edge, and the principle of belief enhancement/withdrawal, which adjusts this value according to the edge content in the other input edge map at the same location, by maximizing the similarity between them. These two principles are combined by maximizing a linear positive combination of these two constraints related by a fusion function, to be determined. The latter maximization is achieved using the Euler-Lagrange equations. This method was tested with real data, and the resulting edge maps combining both range and intensity data were found to satisfy both principles