Abstract
BackgroundFingerprint biometrics play an essential role in authentication. It remains a challenge to match fingerprints with the minutiae or ridges missing. Many fingerprints failed to match their targets due to the incompleteness.ResultIn this work, we modeled the fingerprints with Bezier curves and proposed a novel algorithm to detect and restore fragmented ridges in incomplete fingerprints. In the proposed model, the Bezier curves’ control points represent the fingerprint fragments, reducing the data size by 89% compared to image representations. The representation is lossless as the restoration from the control points fully recovering the image. Our algorithm can effectively restore incomplete fingerprints. In the SFinGe synthetic dataset, the fingerprint image matching score increased by an average of 39.54%, the ERR (equal error rate) is 4.59%, and the FMR1000 (false match rate) is 2.83%, these are lower than 6.56% (ERR) and 5.93% (FMR1000) before restoration. In FVC2004 DB1 real fingerprint dataset, the average matching score increased by 13.22%. The ERR reduced from 8.46% before restoration to 7.23%, and the FMR1000 reduced from 20.58 to 18.01%. Moreover, We assessed the proposed algorithm against FDP-M-net and U-finger in SFinGe synthetic dataset, where FDP-M-net and U-finger are both convolutional neural network models. The results show that the average match score improvement ratio of FDP-M-net is 1.39%, U-finger is 14.62%, both of which are lower than 39.54%, yielded by our algorithm.ConclusionsExperimental results show that the proposed algorithm can successfully repair and reconstruct ridges in single or multiple damaged regions of incomplete fingerprint images, and hence improve the accuracy of fingerprint matching.
Highlights
Fingerprint biometrics play an essential role in authentication
Experimental results show that the proposed algorithm can successfully repair and reconstruct ridges in single or multiple damaged regions of incomplete fingerprint images, and improve the accuracy of fingerprint matching
Fingerprint representation Novel fingerprint representation method we propose a new fingerprint representation method based on Bezier curves, which can effectively convert the fingerprint image into a series of points, coordinate texts, achieve a better compression effect, and facilitate subsequent follow-up analysis of incomplete fingerprints based on curve fitting algorithms
Summary
Fingerprint biometrics play an essential role in authentication. It remains a challenge to match fingerprints with the minutiae or ridges missing. Many fingerprints failed to match their targets due to the incompleteness. Biometric recognition technologies have attracted intense attention, and their applications have become widespread [1, 2]. Fingerprints are highly reliable, and forensic experts adopted them routinely in criminal. The fingerprint verification gains its popularity from universality, uniqueness, persistence, high accuracy, and cost-effectiveness [4, 5]. Scientists achieved substantial progress in fingerprint recognition, and complete fingerprints identification achieves high recognition accuracy. Many issues are there to be addressed for the identification with damaged fingerprints [6]. The loss of informative features with the damaged fingerprints lead to low recognition accuracy
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