TR2013-023
A Keypoint Descriptor for Alignment-Free Fingerprint Matching
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- "A Keypoint Descriptor for Alignment-Free Fingerprint Matching", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2013.BibTeX TR2013-023 PDF
- @inproceedings{Garg2013may,
- author = {Garg, R. and Rane, S.},
- title = {A Keypoint Descriptor for Alignment-Free Fingerprint Matching},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2013,
- month = may,
- url = {https://www.merl.com/publications/TR2013-023}
- }
,
- "A Keypoint Descriptor for Alignment-Free Fingerprint Matching", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2013.
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Research Area:
Information Security
Abstract:
Secure fingerprint authentication via encrypted-domain processing imposes constraints on the underlying feature extraction method: Firstly, it requires fixed-length feature vectors to be amenable to computing distances or correlations. Secondly, extra information must be stored in the clear so that the fingerprints can be aligned prior to feature extraction and secure comparison. These constraints potentially restrict the flexibility, increase computational complexity, and even reduce the security of the scheme. We desire feature vectors suitable for encrypted-domain matching while being free of the above constraints. To this end, a local neighborhood is defined around certain detected minutiae points, and features are extracted based on relative locations of close minutia points, local ridge texture and local ridge orientation. The locality of the features provides robustness to rotation and translation. Feature vectors are compared using operations that can be performed using secure primitives. The process of computing the matching scores -- genuine or impostor -- implicitly yields the best alignment without needing to store unencrypted side information at the access control device. The scheme achieves an Equal Error Rate of 1.46% on a proprietary database and 7.86% on the FVC2002 public database.
Related News & Events
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NEWS ICASSP 2013: 9 publications by Jonathan Le Roux, Dehong Liu, Robert A. Cohen, Dong Tian, Shantanu D. Rane, Jianlin Guo, John R. Hershey, Shinji Watanabe, Petros T. Boufounos, Zafer Sahinoglu and Anthony Vetro Date: May 26, 2013
Where: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
MERL Contacts: Dehong Liu; Jianlin Guo; Anthony Vetro; Petros T. Boufounos; Jonathan Le RouxBrief- The papers "Stereo-based Feature Enhancement Using Dictionary Learning" by Watanabe, S. and Hershey, J.R., "Effectiveness of Discriminative Training and Feature Transformation for Reverberated and Noisy Speech" by Tachioka, Y., Watanabe, S. and Hershey, J.R., "Non-negative Dynamical System with Application to Speech and Audio" by Fevotte, C., Le Roux, J. and Hershey, J.R., "Source Localization in Reverberant Environments using Sparse Optimization" by Le Roux, J., Boufounos, P.T., Kang, K. and Hershey, J.R., "A Keypoint Descriptor for Alignment-Free Fingerprint Matching" by Garg, R. and Rane, S., "Transient Disturbance Detection for Power Systems with a General Likelihood Ratio Test" by Song, JX., Sahinoglu, Z. and Guo, J., "Disparity Estimation of Misaligned Images in a Scanline Optimization Framework" by Rzeszutek, R., Tian, D. and Vetro, A., "Screen Content Coding for HEVC Using Edge Modes" by Hu, S., Cohen, R.A., Vetro, A. and Kuo, C.C.J. and "Random Steerable Arrays for Synthetic Aperture Imaging" by Liu, D. and Boufounos, P.T. were presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).