Fingerprint recognition systems have become prevalent in various security applications. However, recent studies have
shown that it is not difficult to deceive the system with fake fingerprints made of silicon or gelatin. The fake fingerprints
have almost the same ridge-valley patterns as ones of genuine fingerprints so that conventional systems are unable to
detect fake fingerprints without a particular detection method. Many previous works against fake fingers required extra
sensors; thus, they lacked practicality. This paper proposes a practical and effective method that detects fake fingerprints,
using only an image sensor. Two criteria are introduced to differentiate genuine and fake fingerprints: the histogram
distance and Fourier spectrum distance. In the proposed method, after identifying an input fingerprint of a user, the
system computes two distances between the input and the reference that comes from the registered fingerprints of the
user. Depending on the two distances, the system classifies the input as a genuine fingerprint or a fake. In the experiment,
2,400 fingerprint images including 1,600 fakes were tested, and the proposed method has shown a high recognition rate
of 95%. The fake fingerprints were all accepted by a commercial system; thus, the use of these fake fingerprints qualifies
the experiment.
Fractional correlation is an extension of the conventional correlation. It employs fractional Fourier transform (FRFT) that includes the conventional Fourier transform as a special case where the order of the FRFT equals one. Because of the FRFT's lack of the shift-invariant property, the FRFT is not applicable to the conventional joint transform correlator, but to the nonconventional joint transform correlator (NJTC) that have been proposed by F. T. S. Yu et al., in which separate lenses transform the input signals and their spectral distributions overlap on the square-law detector. This provides an optical implementation of the fractional correlation. The conventional Fourier transform generally yields a high peak at the center of the spectral plane. But the FRFT gives a spectral distribution with no high peak, which is desirable because the square-law detector has a finite dynamic range for the linearity. Moreover, we prove that the fractional correlation produces a narrower output distribution and has the same correlation value at the center of the output plane as the conventional correlation. The conventional correlation has the shift-invariant property, but the fractional correlation has not.
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