Generating Cancelable Fingerprint Templates

By Nalini K. Ratha, Sharat Chikkerur, J. Connell, Ruud M. Bolle. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007

953 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/3c0f7caec87e0a1c6dbee1d62c8d1f5e9a760d15

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Citations in the corpus

Cancelable Biometrics: A review (2015, background): “The idea is to morph the original biometric templates by applying signal domain or feature domain transformations [3], [4], [5].”
Fingerprint-Based Fuzzy Vault: Implementation and Performance (2007, methodology): “When multiple impressions are available for vault encoding, we apply a mosaicing technique [37] to combine the minutiae and helper data from the individual images into a single mosaiced template and helper set.”
A survey on biometric cryptosystems and cancelable biometrics (2011, methodology): “, fingerprints in [140] or iris in [138]) is utilized to generate cancelable templates the computational effort of reconstructing (parts of) the original biometric data has to be estimated.”
An evaluation of indirect attacks and countermeasures in fingerprint verification systems (2011, background): “Some notable examples at the feature extraction phase are non-invertible transforms or cancelable biometrics (Ratha et al., 2007) which may be combined with cryptography or other logical countermeasures.”
Biometric Template Security (2008, methodology): “For the functional transformation, we used a mixture of 24 Gaussians with the same isotropic standard deviation of 30 pixels (where the peaks can correspond to +1 or −1 as used in [52]) for calculating the displacement and used the direction of gradient of the mixture of Gaussian function as the dir”
An Analysis of Random Projection for Changeable and Privacy-Preserving Biometric Verification (2010, background): “[17] introduced a framework of generating cancelable fingerprint templates.”
Security algorithm of face recognition based on local binary pattern and random projection (2010, positive): “[6] proposed and analyzed three non-invertible transforms for generating cancelable fingerprint templates.”
Multibiometric Cryptosystems Based on Feature-Level Fusion (2012, background): “A. K. Jain is with the Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824 USA, and also with the Department of Brain and Cognitive Engineering, Korea University, Seoul 136- 713, Republic of Korea (e-mail: jain@cse.msu.edu).”