From Template to Image: Reconstructing Fingerprints from Minutiae Points

By Arun A. Ross, Jidnya Shah, Anil K. Jain. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007

322 citations recorded by the source corpus.

Most fingerprint-based biometric systems store the minutiae template of a user in the database. It has been traditionally assumed that the minutiae template of a user does not reveal any information about the original fingerprint. In this paper, we challenge this notion and show that three levels of information about the parent fingerprint can be elicited from the minutiae template alone, viz., 1) the orientation field information, 2) the class or type information, and 3) the friction ridge structure. The orientation estimation algorithm determines the direction of local ridges using the evidence of minutiae triplets. The estimated orientation field, along with the given minutiae distribution, is then used to predict the class of the fingerprint. Finally, the ridge structure of the parent fingerprint is generated using streamlines that are based on the estimated orientation field. Line integral convolution is used to impart texture to the ensuing ridges, resulting in a ridge map resembling the parent fingerprint. The salient feature of this noniterative method to generate ridges is its ability to preserve the minutiae at specified locations in the reconstructed ridge map. Experiments using a commercial fingerprint matcher suggest that the reconstructed ridge structure bears close resemblance to the parent fingerprint

Subfields: Computer Vision and Pattern Recognition, Environmental Engineering, Signal Processing

View Paper: https://www.semanticscholar.org/paper/2fa66014f0a133c9dae7512e3ceb244ee8c1e311

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Citations in the corpus

Biometric Template Security (2008, background): “Attacks on the template can lead to the following three vulnerabilities: (i) A template can be replaced by an impostors’s template to gain unauthorized access, (ii) A physical spoof can be created from the template (see [34]– [36]) to gain unauthorized access to the system (as well as other systems ”
A Survey on Anti-Spooﬁng Schemes for Fingerprint Recognition Systems (2014, result): “Reversibility of minutiae templates has been demonstrated in several works [Ross et al. 2007; Maltoni et al. 2003; Hill 2001; Galbally et al. 2008; Franco and Maltoni 2008].”
Security and privacy in electronic health records: A systematic literature review (2013, background): “Recent research indicates that the fingerprint minutiae can be used to recover fingerprints [108].”
A survey on biometric cryptosystems and cancelable biometrics (2011, background): “While the industry has long claimed that one of the primary benefits of biometric templates is that original biometric signals acquired to enroll a data subject cannot be reconstructed from stored templates, several approaches [2,3] have proven this claim wrong.”
Guessing human-chosen secrets (2012, background): “Biometrics are any means for identifying humans by difficult-to-forge physiological traits, which may be physical traits such as iris patterns [76], fingerprints [253], or facial structure [192], or behavioural traits such as a user’s voice [18], handwriting [25], or typing style [210].”
Cracking Fuzzy Vaults and Biometric Encryption (2007, background): “Recent work [ 1 ] has shown that recovering biometric data from templates is possible, thus leading us to a stronger motivation for protection.”