Robust fingerprint identification

Due to the complex distortions involved in two impressions of the same finger, fingerprint identification is still a challenging problem for person authentication. In this paper, we propose a fingerprint identification approach based on the triplets of minutiae. The features that we use to find the potential corresponding triangles include angles, triangle orientation, triangle direction, maximum side, minutiae density and ridge counts. False corresponding triangles are eliminated by applying constraints to the transformation between two potential corresponding triangles. The experimental results on National Institute of Standards and Technology special fingerprint database 4, NIST-4, show that, as compared to the linear search, the proposed approach provides a reduction by a factor of 200 for the number of the hypotheses that need to be considered and it can achieve good performance even when a large portion of fingerprints in the database are of poor quality.