Corpus ID: 199064428

OCT Fingerprints: Resilience to Presentation Attacks

  title={OCT Fingerprints: Resilience to Presentation Attacks},
  author={T. Chugh and Anil K. Jain},
Optical coherent tomography (OCT) fingerprint technology provides rich depth information, including internal fingerprint (papillary junction) and sweat (eccrine) glands, in addition to imaging any fake layers (presentation attacks) placed over finger skin. Unlike 2D surface fingerprint scans, additional depth information provided by the cross-sectional OCT depth profile scans are purported to thwart fingerprint presentation attacks. We develop and evaluate a presentation attack detector (PAD… Expand
Surface and Internal Fingerprint Reconstruction From Optical Coherence Tomography Through Convolutional Neural Network
A modified U-Net that combines residual learning, bidirectional convolutional long short-term memory and hybrid dilated convolution (denoted as BCL-U Net) for OCT volume data segmentation and two fingerprint reconstruction approaches are proposed, marking the first time that simultaneous and automatic extraction is performed for surface fingerprint, internal fingerprint and sweat gland. Expand
Fingerprint Presentation Attack Detection: A Sensor and Material Agnostic Approach
This study builds on top of any CNN-based architecture trained for fingerprint spoof detection combined with cross-material spoof generalization using a style transfer network wrapper and incorporates adversarial representation learning (ARL) in deep neural networks (DNN) to learn sensor and material invariant representations for PAD. Expand
Fingerprint Spoof Detection: Temporal Analysis of Image Sequence
  • T. Chugh, Anil K. Jain
  • Computer Science
  • 2020 IEEE International Joint Conference on Biometrics (IJCB)
  • 2020
We utilize the dynamics involved in the imaging of a fingerprint on a touch-based fingerprint reader, such as perspiration, changes in skin color (blanching), and skin distortion, to differentiateExpand
Multi-Modal Fingerprint Presentation Attack Detection: Evaluation on a New Dataset
The results indicate that the power of the approach stems from the nature of the captured data rather than the employed classification framework, which justifies the extra cost for hardware-based (or hybrid) solutions. Expand
Analysing the Performance of LSTMs and CNNs on 1310 nm Laser Data for Fingerprint Presentation Attack Detection
An evaluation of three long short-term memory (LSTM) networks in comparison to eight convolutional neural networks (CNNs) on a database comprising over 22,000 samples and including 45 different PAI species shows that the diversity ofPAI species is too big for a single classifier to correctly detect all presentation attacks. Expand
One-Class Fingerprint Presentation Attack Detection Using Auto-Encoder Network
A novel One-Class PAD (OCPAD) method for Optical Coherence Technology (OCT) images based fingerprint PA detection and can achieve a True Positive Rate (TPR) of 99.43% when the False Positive rate equals to 10% and a TPR of 96.59% when FPR=5%, which significantly outperformed a feature based approach and a supervised learning based model requiring PAs for training. Expand
Fingerprint Presentation Attack Detection by Channel-wise Feature Denoising
  • Feng Liu, Zhe Kong, Haozhe Liu, Wentian Zhang, Linlin Shen
  • Computer Science
  • ArXiv
  • 2021
Due to the diversity of attack materials, fingerprint recognition systems (AFRSs) are vulnerable to malicious attacks. It is of great importance to propose effective Fingerprint Presentation AttackExpand
Fingerprint Spoof Detector Generalization
We present a style-transfer based wrapper, called Universal Material Generator (UMG), to improve the generalization performance of any fingerprint spoof (presentation attack) detector against spoofsExpand
Fingerprint Spoof Generalization
We present a style-transfer based wrapper, called Universal Material Generator (UMG), to improve the generalization performance of any fingerprint spoof detector against spoofs made from materialsExpand
Towards Fingerprint Spoofing Detection in the Terahertz Range
The terahertz technology can be successfully applied for spoofing detection with high detection probability and the skin structure of the finger pad is described with a focus on the outermost stratum corneum. Expand


Optical Coherence Tomography for Fingerprint Presentation Attack Detection
New research in fingerprint biometrics uses optical coherence tomography (OCT) technology to acquire fingerprints from where they originate below the surface of the skin, and this work serves to detail current research in this domain. Expand
Defense of fake fingerprint attacks using a swept source laser optical coherence tomography setup
It is demonstrated that OCT is a very useful tool to enhance the performance of biometric control systems concerning attacks by thin layer fingerprint fakes. Expand
High-accurate and robust fingerprint anti-spoofing system using Optical Coherence Tomography
Experimental results show that the proposed anti- Spoofing system could achieve 100% accuracy over all four types of artificial fingerprints and outperform the other automated anti-spoofing method in comparison. Expand
Biometric Mapping of Fingertip Eccrine Glands With Optical Coherence Tomography
  • M. Liu, T. Buma
  • Computer Science
  • IEEE Photonics Technology Letters
  • 2010
This work proposes a more reliable biometric technology using spectral domain optical coherence tomography (SD-OCT) to image the subsurface of a fingertip and demonstrates high repeatability in clearly visualizing the distribution of sweat (eccrine) glands in live fingertips. Expand
LivDet 2017 Fingerprint Liveness Detection Competition 2017
Since from 2009, the Fingerprint Liveness Detection Competition (LivDet) aims to assess the performance of the state-of-the-art algorithms according to a rigorous experimental protocol and, at the same time, a simple overview of the basic achievements. Expand
Fingerprint spoof detection using minutiae-based local patches
A deep convolutional neural network based approach utilizing local patches extracted around fingerprint minutiae provides state of the art accuracies in fingerprint spoof detection for intra-sensor, cross-material,cross-s sensor, as well as cross-dataset testing scenarios. Expand
Towards Fingerprint Presentation Attack Detection Based on Convolutional Neural Networks and Short Wave Infrared Imaging
A new fingerprint presentation attack detection method based on convolutional neural networks and multi-spectral images extracted from the finger in the short wave infrared spectrum is presented. Expand
Fingerprint Presentation Attack Detection: Generalization and Efficiency
It is observed that a set of six PA materials, namely Silicone, 2D Paper, Play Doh, Gelatin, Latex Body Paint and Monster Liquid Latex provide a good representative set that should be included in training to achieve generalization of PAD. Expand
Internal Fingerprint Identification With Optical Coherence Tomography
Existing biometric fingerprint devices show numerous reliability problems such as wet or fake fingers. In this letter, a secured method using the internal structures of the finger (papillary layer)Expand
Fingerprint Spoof Buster: Use of Minutiae-Centered Patches
A deep convolutional neural network-based approach utilizing local patches centered and aligned using fingerprint minutiae provides the state-of-the-art accuracies in fingerprint spoof detection for intra-sensor, cross-material,cross-s sensor, as well as cross-dataset testing scenarios. Expand