Fingerprint Registration Using Minutia Clusters and Centroid Structure 1

In this paper a novel distortion-tolerant fingerprint registration method based on clustering is proposed. In this method, minutiae features of the query fingerprint are divided into various clusters. Several local structure transformations are estimated by local structure sets. Then the global structures (centroid structures) are constructed according to the local structure transformation. The global transformation is determined by the score of local structure transformation together with the similarity level of the global structure. Experimental results show that this algorithm is robust for aligning fingerprints with a small number of minutia and heavy distortions. Such situations are often encountered in forensic applications