Advances in fingerprint authentication technology have led to it being used in a growing range of personal devices such as PCs and smartphones. However, they have also made it possible to capture fingerprints remotely with a digital camera, putting the target person at risk of illegal log-ins and identity theft. This article shows how fingerprint captured in this manner can be authenticated and how people can protect their fingerprints against surreptitious photography. First we show that photographed fingerprints have enough information to spoof fingerprint authentication systems by demonstrating with “fake fingers” made from such photographs. Then we present a method that defeats the use of surreptitious photography without preventing the use of legitimate fingerprint authentication devices. Finally, we demonstrate that an implementation of the proposed method called “BiometricJammer,” a wearable device put on a fingertip, can effectively prevent the illegal acquisition of fingerprints by surreptitious photography while still enabling contact-based fingerprint sensors to respond normally.

Orientation field (OF) estimation is a fundamental process in fingerprint authentication systems. In this paper, a novel binary pattern based low-cost OF estimation algorithm is proposed. The new method consists of two modules. The first is block-level orientation estimation and averaging in vector space by pixel level orientation statistics. The second is orientation quantization and smoothing. In the second module, the continuous orientation is quantized into fixed orientations with sufficient resolution (interval between fixed orientations). An effective smoothing scheme on the quantized orientation space is also proposed. The proposed algorithm is capable of stably processing poor-quality fingerprint images and is validated by tests conducted on an adaptive OF matching scheme. The proposed algorithm is also implemented into a fingerprint System on Chip (SoC) to comfirm that it satisfies the strict requirements of embedded system.

A novel binary line-pattern algorithm for embedded fingerprint authentication system is introduced in this paper. In this algorithm, each line-pattern is a one-dimension binary matrix that describes the alternation pattern of ridge and valley in fingerprint image. Two parallel lines or two cross lines in a certain scope make up related line-pattern pair. Several such line-pattern pairs at different parts of a fingerprint image can describe another intrinsic feature besides traditional minutiae feature. Experimental results showed this algorithm was not only efficient but also effective. Furthermore, a hybrid fingerprint match scheme is also introduced in this paper. It has the following features: (i) minutiae matching is firstly carried out to calculate the similarity score between the query fingerprint and the template fingerprint, and moreover, the translation and rotation parameters are obtained at the same time; (ii) line-pattern algorithm is immediately performed based on the parameters obtained after minutiae matching to get another similarity score; (iii) the final matching score is the combination of the minutiae matching score and the line-pattern matching score. Experiments were conducted on the FVC2002 database and our private database respectively. Both of the results were inspiring. In detail, at the same FAR value, the FRR of this hybrid match algorithm is to be 2-8% lower than only minutiae-based matching algorithm.