Fingerprint pattern classification
Pattern Recognition
Instance-Based Learning Algorithms
Machine Learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society
Machine Learning
The Alternating Decision Tree Learning Algorithm
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
Information fusion in biometrics
Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)
Enhancing security and privacy in biometrics-based authentication systems
IBM Systems Journal - End-to-end security
Liveness Detection for Fingerprint Scanners Based on the Statistics of Wavelet Signal Processing
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Vitality Detection from Fingerprint Images: A Critical Survey
ICB '07 Proceedings of the international conference on Advances in Biometrics
Fingerprint Liveness Detection Using Curvelet Energy and Co-Occurrence Signatures
CGIV '08 Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation
Liveness detection of fingerprint based on band-selective Fourier spectrum
ICISC'07 Proceedings of the 10th international conference on Information security and cryptology
Fake finger detection based on time-series fingerprint image analysis
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Analysis and selection of features for the fingerprint vitality detection
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Fake finger detection by skin distortion analysis
IEEE Transactions on Information Forensics and Security
Time-series detection of perspiration as a liveness test in fingerprint devices
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A new approach to fake finger detection based on skin elasticity analysis
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Fake finger detection based on thin-plate spline distortion model
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Interacting with Computers
Multi-scale local binary pattern with filters for spoof fingerprint detection
Information Sciences: an International Journal
| Hi-index | 0.01 |
Biometric fingerprint scanners are positioned to provide improved security in a great span of applications from government to private. However, one highly publicized vulnerability is that it is possible to spoof a variety of fingerprint scanners using artificial fingers made from Play-Doh, gelatin and silicone molds. Therefore, it is necessary to offer protection for fingerprint systems against these threats. In this paper, an anti-spoofing detection method is proposed which is based on ridge signal and valley noise analysis, to quantify perspiration patterns along ridges in live subjects and noise patterns along valleys in spoofs. The signals representing gray level patterns along ridges and valleys are explored in spatial, frequency and wavelet domains. Based on these features, separation (live/spoof) is performed using standard pattern classification tools including classification trees and neural networks. We test this method on a larger dataset than previously considered which contains 644 live fingerprints (81 subjects with 2 fingers for an average of 4 sessions) and 570 spoof fingerprints (made from Play-Doh, gelatin and silicone molds in multiple sessions) collected from the Identix fingerprint scanner. Results show that the performance can reach 99.1% correct classification overall. The proposed anti-spoofing method is purely software based and integration of this method can provide protection for fingerprint scanners against gelatin, Play-Doh and silicone spoof fingers.