Spectral correspondence method for fingerprint minutia matching

This paper presents a spectral correspondence method for fingerprint matching. Minutia matching is formulated as recovering the dense sub-block in the corresponding matrix. And then the spectral correspondence method is used for searching the dense sub-block. First, we propose the pairwise adjacency matrix (PAM), whose diagonal elements represent similarities of minutia structures and other elements represent pairwise compatibilities between local minutia structure pair. Second, correct minutia pairs are likely to establish both large similarities and large compatibilities among each other and they form a dense sub-block. Then minutia matching is formulated as recovering the dense sub-block in the PAM. It gives a clear mathematical meaning for “optimal matching minutia pairs”. Third, we recover the dense sub-block based on spectral correspondence method, by using the principal eigenvector of PAM and imposing the one-to-one mapping constraints. Proposed method has stronger description ability and better robustness. Experiments conducted on FVC database demonstrate the effectiveness and the efficiency.