Latent Fingerprint Matching Using Distinctive Ridge Points

Abstract

The way that forensic examiners compare fingerprints highly differs from the behaviour of current automatic fingerprint identification algorithms. Experts usually use all the information in the fingerprint, not only minutiae, while automatic algorithms don’t. Partial (especially latent) fingerprint matching algorithms still report low accuracy values in comparison to those achieved by experts. This difference is mainly due to the features used in each case. In this work, a novel approach for matching partial fingerprints is presented. We introduce a new fingerprint feature, named Distinctive Ridge Point (DRP), combined with an improved triangle-based representation which also uses minutiae. The new feature describes the neighbouring ridges of minutiae in a novel way. A modified version of a fingerprint matching algorithm presented in a previous work is used for matching two triangular representations of minutiae and DRPs. The experiments conducted on NIST27 database with a background added of 29000 tenprint impressions from NIST14 and NIST4 databases showed the benefits of this approach. The results show that using the proposal we achieved an accuracy of 70.9% in rank-1, improving in an 11% the accuracy obtained using minutiae and the reference point. This result is comparable with the best accuracy reached in the state of the art while the amount of features is reduced.