Fingerprint Liveness Detection Using Curvelet Energy and Co-Occurrence Signatures

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Robust multimodal face and fingerprint fusion in the presence of spoofing attacks (2016, methodology): “The ﬁ rst category assessing textural properties is the more widespread group with approaches like LBP [24], or statistical features [25] exploiting the observation that images/videos with spoofed faces (printed or replayed) do not exhibit the same noise-level like genuine samples.”
Fingerprint liveness detection by local phase quantization (2012, background): “Several approaches have been proposed so far, but none of them have shown to reach an very low error rate [1, 2, 3, 4, 5, 6, 7].”
A Survey on Anti-Spooﬁng Schemes for Fingerprint Recognition Systems (2014, methodology): “First, the gray value of the center pixel of the circularly symmetric neighbor set is subtracted from the gray values of the circularly symmetric neighborhood [Nikam and Agarwal 2008b] [Martins et al. 2012].”