Partial fingerprint indexing: a combination of local and reconstructed global features

Existing work on partial fingerprint indexing attempts to make full use of the extracted features from the partial segments, such as singular points, minutiae, orientation field, and ridge count. However, singular points may not exist in partial fingerprints, and none of these features can form a complete set of feature vectors that can be used for matching with those derived from the corresponding full fingerprints for indexing. Our former work on fingerprint orientation model based on two-dimensional Fourier expansion (FOMFE) coefficients-based fingerprint indexing and global orientation field reconstruction has demonstrated the possibility of reconstructing a global feature vector for partial fingerprint indexing. In this paper, we design some novel features of minutiae triplets in addition to some commonly used features to constitute the local minutiae triplet features. Experiments carried out on fingerprint verification competition (FVC) 2000 DB2a, FVC 2002 DB1a, and National Institute of Standards and Technology (NIST) SD 14 demonstrate the performance improvement after adding the new features to minutiae triplet feature set. We then propose to combine the reconstructed global feature and local minutiae triplet features to improve the performance of partial fingerprint indexing. Specifically, the minutiae triplet-based indexing scheme and the FOMFE coefficients-based indexing scheme are applied separately to generate two candidate lists; then, a fuzzy-based fusion scheme is designed to generate the final candidate list for matching. Experiments carried out on the public database NIST SD 14 show that the proposed approach can improve the performance that has been achieved by individual partial fingerprint indexing algorithms before fusion.