From the early days of the mid to late nineteenth century when scientific research first began to focus on fingerprints, to the present day fingerprint recognition systems we find deployed on our day to day devices, the science of fingerprint recognition has come a long way. In spite of this progress, there remains challenging problems to be solved. This thesis highlights a few of these problems, and proposes solutions to address them. One area of further research that must be conducted on fingerprint recognition systems is that of robust, operational evaluations. In chapter two of this thesis, we show how the current practices of using calibration patterns to evaluate fingerprint readers are limited. We then propose a realistic fake finger called the Universal Target. The Universal Target is a realistic, 3D, fake finger (or phantom) which can be imaged by all major types of fingerprint sensing technologies. We show the entire manufacturing (molding and casting) process for fabricating the Universal Targets. Then, we show a series of evaluations which demonstrate how the Universal Targets can be used to operationally evaluate current commercial fingerprint readers. Our Universal Target is a significant step forward in enabling more realistic, standardized evaluations of fingerprint readers. In our third chapter, we shift gears from improving the evaluation standards of fingerprint readers to instead focus on the security of fingerprint readers. In particular, we turn our attention towards detecting fake fingerprint (spoof) attacks. To do so, we open source a fingerprint reader (built from low-cost ubiquitous components), called RaspiReader. RaspiReader is a high-resolution fingerprint reader customized with both direct-view imaging and FTIR imaging in order to better detect fingerprint spoofs. We show through a number of experiments that RaspiReader enables state-of-the-art fingerprint spoof detection accuracy. We also demonstrate that RaspiReader enables better generalization to what are known as "unseen attacks" (those attacks which were not seen during training of the spoof detector). Finally, we show that fingerprints captured by RaspiReader are completely compatible with images captured by legacy fingerprint readers for matching.In chapter four, we move on to propose a major improvement to the fingerprint feature extraction and matching sub-modules of fingerprint recognition systems. In particular, we propose a deep network, called DeepPrint, to extract a 200 byte fixed-length fingerprint representation. While prevailing fingerprint matchers primarily utilize minutiae points and expensive graph matching algorithms for comparison, two DeepPrint representations can be compared with only 192 multiplications and 191 additions. This is extremely useful for large scale search where potentially billions of pairwise fingerprint comparisons must be made. The DeepPrint representation also enables practical encrypted matching using a fully homomorphic encryption scheme. This enables better protection of the fingerprint templates which are stored in the database. While discriminative fixed-length representations are available for both face and iris recognition, such a representation has eluded fingerprint recognition. This chapter aims to fill that void.Finally, we conclude our thesis by working to extend fingerprint recognition to all ages. While current fingerprint recognition systems are being used by billions of teenagers and adults around the world, the youngest people among us remain disenfranchised. In particular, modern day fingerprint recognition systems do not work well on infants and young children. In this penultimate chapter, we aim to rectify this major shortcoming. To that end, we prototype a high-resolution (1900 ppi) infant fingerprint reader. Then, we track and fingerprint 315 infants (under the age of 3 months at enrollment) at the Dayalbagh Children's Hospital in Agra India over the course of 1 year (4 different sessions). To match the infant fingerprints, we develop our own high-resolution infant fingerprint matcher. Our experimental results demonstrate significant promise for the extension of fingerprint recognition to all ages. This work has the potential for major global good as all young infants and children could be given a verifiable digital identity for better vaccination tracking as a child and for government benefits and assistance as an adult. In summary, this thesis makes major contributions to the entire end-to-end fingerprint recognition system and extends its use case to all ages.
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