Evaluating the Operational Impact of Contactless Fingerprint Imagery on Matcher Performance
Shahram Orandi, John M. Libert, Bruce Bandini, Kenneth Ko, John D. Grantham, Craig I. Watson
This study set out to examine the operational impact of introducing contactless fingerprint imagery to a modern fingerprint matching system that was designed for touch-collected images in either a standard Ten-Print operational matching pathway or a Mobile ID optimized operational pathway, depending on configuration. Contactless fingerprint imagery from six contactless devices were used, along with mated imagery from two touch-based devices using a block experimental design. Experimental cases were defined for the matching of contactless fingerprint imagery as either probe or biometric reference database, and system matching accuracy measured in terms of false negative identification rate (FNIR). Due to the small data set available, the experiment was not structured to measure false positive error rates. Results showed the viability of using contactless imagery as the biometric reference database, albeit using these images will come at the price of matching accuracy on the Ten-Print matcher (FNIR of 0.5 % worst case for touch devices vs. FNIR of 1.6 % best case for contactless). The Mobile ID matcher seemed to close the gap between contactless and touch with the best performing contactless device in terms of accuracy (D3) performing at an FNIR of 0.8 % while the worst performing touch-to-touch device was measured at FNIR of 0.5 % showing that Mobile ID optimizations may be key in the introduction of contactless into existing matching pathways. Finally, the introduction of contactless imagery did incur a larger throughput penalty on the Ten- Print matcher than it did on the Mobile ID operational matcher.
, Libert, J.
, Bandini, B.
, Ko, K.
, Grantham, J.
and Watson, C.
Evaluating the Operational Impact of Contactless Fingerprint Imagery on Matcher Performance, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.IR.8315
(Accessed May 21, 2022)