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In this paper we define a new approach to biometric fusion, characterized by the use of graph structure to represent identities, starting from a hybrid rank-score fusion level.
We define the proposed framework, with the description of the mapping identity-list-graph, with the use of the cohort theory, and then we explain the steps to perform the Graph Similarity Score and the Graph Based Fusion and their computational complexity.
Subsequently, we apply the proposed method to two different dataset, in order to evaluate its accuracy and to compare the obtained results against the employment of the other fusion schemes previously illustrated, and then we analyze the results themselves, even by means of a Case Study.
Finally we make reflections about what has been achieved and which could be the possible future works exploiting our framework.