Partial fingerprint identification for large databases
- Javad Khodadoust, Ali Mohammad Khodadoust
- Pattern Analysis and Applications
In this paper, we propose a novel method for fingerprint indexing based on local patterns of ridge flow centered on minutiae. These local descriptors are projected on a learned dictionary of ridge flow patches, with a sparsity-inducing algorithm. We show that this sparse decomposition allows to replace the ridge flow patches by a compressed signature with a reduced loss of accuracy. We experimented the combination of these descriptors with the formerly known Minutiae Cylinder Code (MCC) descriptor, that provides another kind of local information. Then, we show that the combination of these descriptors performs well for fast nearest neighbor search algorithms based on Locality-Sensitive Hashing (LSH), and allows to either to improve the accuracy of the state-of-the-art algorithm, or to improve its computational efficiency.