A fingerprint retrieval system based on level-1 and level-2 features
Expert Systems with Applications: An International Journal
Fingerprint indexing with bad quality areas
Expert Systems with Applications: An International Journal
Indexing and retrieving in fingerprint databases under structural distortions
Expert Systems with Applications: An International Journal
Fusion of finger types for fingerprint indexing using minutiae quadruplets
Pattern Recognition Letters
| Hi-index | 0.15 |
This paper proposes a new hash-based indexing method to speed up fingerprint identification in large databases. A Locality-Sensitive Hashing (LSH) scheme has been designed relying on Minutiae Cylinder-Code (MCC), which proved to be very effective in mapping a minutiae-based representation (position/angle only) into a set of fixed-length transformation-invariant binary vectors. A novel search algorithm has been designed thanks to the derivation of a numerical approximation for the similarity between MCC vectors. Extensive experimentations have been carried out to compare the proposed approach against 15 existing methods over all the benchmarks typically used for fingerprint indexing. In spite of the smaller set of features used (top performing methods usually combine more features), the new approach outperforms existing ones in almost all of the cases.