Randomized approach with geometric constraints to fingerprint verification

In this paper, a fuzzy bipartite weighted graph model is proposed to solve fingerprint verification problem. A fingerprint image is preprocessed first to form clusters of feature points, which are called feature point clusters. Twenty-four attributes are extracted for each feature point cluster. The attributes are characterized by fuzzy values. Attributes of an input image to be verified are considered as the set of left nodes in a fuzzy bipartite weighted graph, and the attributes of claimed template fingerprint image are considered as the set of right nodes in the graph. The fingerprint verification problem is thus converted into a fuzzy bipartite weighted graph matching problem. A matching algorithm is proposed for the fuzzy bipartite weighted graph model to find an optimal matching with a goodness score. Experimental results reveal the feasibility of the proposed approach in fingerprint verification.