Unsupervised Texture Segmentation Using Markov Random Field Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
The nature of statistical learning theory
The nature of statistical learning theory
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
IEEE Transactions on Pattern Analysis and Machine Intelligence
Biometrical fingerprint recognition: don't get your fingers burned
Proceedings of the fourth working conference on smart card research and advanced applications on Smart card research and advanced applications
Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Alternating Decision Tree Learning Algorithm
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
An Analysis of Minutiae Matching Strength
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Enhancing security and privacy in biometrics-based authentication systems
IBM Systems Journal - End-to-end security
Visual learning of texture descriptors for facial expression recognition in thermal imagery
Computer Vision and Image Understanding
Fake fingerprint detection by odor analysis
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
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
Filterbank-based fingerprint matching
IEEE Transactions on Image Processing
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Perspiration-based liveness detection method is slow, as it requires two consecutive fingerprints to notice perspiration. Some other methods in the literature need extra hardware to detect liveness. To alleviate the problems, a single-image method using fusion of Gabor features and grey level cooccurrence probability (GLCP) features is proposed. It is based on the observation that, real and spoof fingerprints exhibit different textural characteristics. Dimensionality of the features is reduced by principal component analysis (PCA). We test feature sets on three classifiers: AdaBoost.M1, support vector machine and alternating decision tree; then we fuse all the classifiers using the 'Max Rule' to form an ensemble classifier. Fused feature set is found to produce higher accuracy (∼98.35% classification rate) relative to the individual feature sets (classification accuracy ranges from ∼93.88% to ∼96.71%). Thus, the performance of new liveness detection approach is very promising, as it needs only one fingerprint and no extra hardware to detect vitality.