3D fingerprint phantoms. Arora, S., S., Cao, K., Jain, A., K., & Paulter, N., G. In Proceedings of the International Conference on Pattern Recognition (ICPR), pages 684-689, 2014.
3D fingerprint phantoms [link]Website  abstract   bibtex   
One of the critical factors prior to deployment of any large scale biometric system is to have a realistic estimate of its matching performance. In practice, evaluations are conducted on the operational data to set an appropriate threshold on match scores before the actual deployment. These performance estimates, though, are restricted by the amount of available test data. To overcome this limitation, use of a large number of 2D synthetic fingerprints for evaluating fingerprint systems had been proposed. However, the utility of 2D synthetic fingerprints is limited in the context of testing end-to-end fingerprint systems which involve the entire matching process, from image acquisition to feature extraction and matching. For a comprehensive evaluation of fingerprint systems, we propose creating 3D fingerprint phantoms (phantoms or imaging phantoms are specially designed objects with known properties scanned or imaged to evaluate, analyze, and tune the performance of various imaging devices) with known characteristics (e.g., type, singular points and minutiae) by (i) projecting 2D synthetic fingerprints with known characteristics onto a generic 3D finger surface and (ii) printing the 3D fingerprint phantoms using a commodity 3D printer. Preliminary experimental results show that the captured images of the 3D fingerprint phantoms can be successfully matched to the 2D synthetic fingerprint images (from which the phantoms were generated) using a commercial fingerprint matcher. This demonstrates that our method preserves the ridges and valleys during the 3D fingerprint phantom creation process ensuring that the synthesized 3D phantoms can be utilized for comprehensive evaluations of fingerprint systems.
@inProceedings{
 title = {3D fingerprint phantoms},
 type = {inProceedings},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {attack,fingerprint},
 pages = {684-689},
 websites = {http://dx.doi.org/10.1109/ICPR.2014.128},
 institution = {IEEE},
 id = {2e70c04a-3f8a-382c-b693-4e907b5fc4bb},
 created = {2018-07-12T21:32:31.299Z},
 file_attached = {false},
 profile_id = {f954d000-ce94-3da6-bd26-b983145a920f},
 group_id = {b0b145a3-980e-3ad7-a16f-c93918c606ed},
 last_modified = {2018-07-12T21:32:31.299Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {arora:fingerprint14},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {One of the critical factors prior to deployment of any large scale biometric system is to have a realistic estimate of its matching performance. In practice, evaluations are conducted on the operational data to set an appropriate threshold on match scores before the actual deployment. These performance estimates, though, are restricted by the amount of available test data. To overcome this limitation, use of a large number of 2D synthetic fingerprints for evaluating fingerprint systems had been proposed. However, the utility of 2D synthetic fingerprints is limited in the context of testing end-to-end fingerprint systems which involve the entire matching process, from image acquisition to feature extraction and matching. For a comprehensive evaluation of fingerprint systems, we propose creating 3D fingerprint phantoms (phantoms or imaging phantoms are specially designed objects with known properties scanned or imaged to evaluate, analyze, and tune the performance of various imaging devices) with known characteristics (e.g., type, singular points and minutiae) by (i) projecting 2D synthetic fingerprints with known characteristics onto a generic 3D finger surface and (ii) printing the 3D fingerprint phantoms using a commodity 3D printer. Preliminary experimental results show that the captured images of the 3D fingerprint phantoms can be successfully matched to the 2D synthetic fingerprint images (from which the phantoms were generated) using a commercial fingerprint matcher. This demonstrates that our method preserves the ridges and valleys during the 3D fingerprint phantom creation process ensuring that the synthesized 3D phantoms can be utilized for comprehensive evaluations of fingerprint systems.},
 bibtype = {inProceedings},
 author = {Arora, Sunpreet S and Cao, Kai and Jain, Anubhav K and Paulter, Nicholas G},
 booktitle = {Proceedings of the International Conference on Pattern Recognition (ICPR)}
}

Downloads: 0