Using the Number of Pores on Fingerprint Images to Detect Spoofing Attacks

Due to the growing use of biometric technologies in our modern society, spoofing attacks are becoming a serious concern. Many solutions have been proposed to detect the use of fake "fingerprints" on an acquisition device. In this paper, we propose to take advantage of intrinsic features of friction ridge skin: pores. The aim of this study is to investigate the potential of using pores to detect spoofing attacks. Results show that the use of pores is a promising approach. Four major observations were made: First, results confirmed that the reproduction of pores on fake "fingerprints" is possible. Second, the distribution of the total number of pores between fake and genuine fingerprints cannot be discriminated. Third, the difference in pore quantities between a query image and a reference image (genuine or fake) can be used as a discriminating factor in a linear discriminant analysis. In our sample, the observed error rates were as follows: 45.5% of false positive (the fake passed the test) and 3.8% of false negative (a genuine print has been rejected). Finally, the performance is improved by using the difference of pore quantity obtained between a distorted query fingerprint and a non-distorted reference fingerprint. By using this approach, the error rates improved to 21.2% of false acceptation rate and 8.3% of false rejection rate.