Fingerprint Matching Using Hierarchical Alignment and Matching Score Weighting

Fingerprint matching is an extremely difficult problem,mainly due to the large variability in different impressions of the same finger.In this paper,a robust fingerprint matching algorithm has been developed.In the alignment stage,short ridges and invariant groups of local feature vectors are used to select corresponding minutiae for the alignment of two minutiae sets efficiently and accurately.In the following stage of matching aligned minutial,a coarse matching set is achieved by the elastic matching algorithm,but there are always some false matching pairs.In order to decrease the effect of false matching pairs to the final result,a novel method is introduced to weight the matching scores,and a more reliable similarity is achieved.Experiments on four databases of FVC2002show that this fingerprint matching technique is more accurate and efficient compared with the conventional approach.