Cancelable Biometric Template Generation Using Convolutional Autoencoder

  title={Cancelable Biometric Template Generation Using Convolutional Autoencoder},
  author={Gourav Siddhad and Pritee Khanna and Aparajita Ojha},
  booktitle={International Conference on Computer Vision and Image Processing},

Max-min threshold-based cancelable biometric templates for low-end devices

In this work, features extracted using Log-Gabor filters are processed according to the proposed max-min thresholding, and the resulting binary features are transformed by random projection on a key matrix to create a cancelable template.



RP-LPP : a random permutation based locality preserving projection for cancelable biometric recognition

A simple and powerful method called Random Permutation Locality Preserving Projection (RP-LPP) for Cancelable Biometric Recognition, which exploits the mathematical relationship between the eigenvalues and eigenvectors of the original biometric image and its randomly permuted version is exploited for carrying out cancelable biometric recognition.

A New Biometric Template Protection using Random Orthonormal Projection and Fuzzy Commitment

This work proposes a novel hybrid biometric template protection which takes benefits of both approaches while preventing their limitations and demonstrates that the performance of the system can be maintained with the support of a new random orthonormal project technique.

Random Distance Method for Generating Unimodal and Multimodal Cancelable Biometric Features

A novel template transformation technique named random distance method is proposed which not only generates discriminative and privacy preserving revocable pseudo-biometric identities, but also reduces their size by 50%.

HiDDeN: Hiding Data With Deep Networks

This work finds that neural networks can learn to use invisible perturbations to encode a rich amount of useful information, and demonstrates that adversarial training improves the visual quality of encoded images.

General Framework to Evaluate Unlinkability in Biometric Template Protection Systems

This paper proposes a new general framework for the evaluation of biometric templates’ unlinkability and applies it to assess the un linkability of the four state-of-the-art techniques for biometric template protection: biometric salting, bloom filters, homomorphic encryption, and block re-mapping.

Cancelable features using log-Gabor filters for biometric authentication

This work proposes a template protection approach which generates revocable binary features from phase and magnitude patterns of log-Gabor filters which is revealed that generated templates are non-invertible, easy to revoke, and also deliver good performance.

Biometric template protection using cancelable biometrics and visual cryptography techniques

This work attempts to summarize the existing approaches in literature making use of Cancelable biometrics and visual cryptography to protect biometric templates to improve public confidence and acceptance of biometric systems.

Contactless and Pose Invariant Biometric Identification Using Hand Surface

A novel approach for hand matching that achieves significantly improved performance even in the presence of large hand pose variations and helps to achieve performance improvement of 60% over the case when matching scores are combined using the weighted sum rule.

Cancelable Biometrics: A review

An overview of various cancelable biometric schemes for biometric template protection is provided and the merits and drawbacks of available cancelableBiometric systems are discussed and promising avenues of research are identified.