Abstract
Most fingerprint recognition techniques are based on minutiae matching and have been well studied. However, this technology still suffers from problems associated with the handling of poor quality impressions. One problem besetting fingerprint matching is distortion. Distortion changes both geometric position and orientation, and leads to difficulties in establishing a match among multiple impressions acquired from the same finger tip. In this paper, according to the particularity of fingerprint distortion, we propose a combined radial basis function (RBF) model, which separately builds rigid and nonrigid transformations, for attacking the distortion problem. Combined RBF model provides more accurate mapping function between a possible matched-pair. Experiments on real data demonstrate the efficacy of the proposed method in improving the compensation of fingerprint distortion.
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