Optimal mapping of graph homomorphism onto self organising Hopfield network

摘要

In a recent paper by us, a novel programming strategy was proposed to obtain homomorphic graph matching using the Hopfield network. Subsequently a self-organisation scheme was also proposed to adaptively learn the constraint parameter which is required to generate the Desired homomorphic mapping for every pair of model and scene data. In this paper, an augmented weighted model attributed relational Graph (WARG0 representation scheme is proposed. The representation scheme incorporates a distinct weighting factor and tolerance Parameter for every model attribute.