Fingerprint verification using SIFT features

Fingerprints are being extensively used for person identification in a number of commercial, civil, and forensic applications. Most of the current fingerprint verification systems utilize features that are based on minutiae points and ridge patterns. While minutiae based fingerprint verification systems have shown fairly high accuracies, further improvements in their performance are needed for acceptable performance, especially in applications involving very large scale databases. In an effort to extend the existing technology for fingerprint verification, we propose a new representation and matching scheme for fingerprint using Scale Invariant Feature Transformation (SIFT). We extract characteristic SIFT feature points in scale space and perform matching based on the texture information around the feature points using the SIFT operator. A systematic strategy of applying SIFT to fingerprint images is proposed. Using a public domain fingerprint database (FVC 2002), we demonstrate that the proposed approach complements the minutiae based fingerprint representation. Further, the combination of SIFT and conventional minutiae based system achieves significantly better performance than either of the individual schemes.