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The present article focuses on the classification of fingerprints. Our aim goal is to unify the process of fingerprint compression, classification and identification. The well known methods suited to these tasks are based on WSQ (Wavelet Scalar Quantization) for compression, Gabor filters for classification and minutiae matching for identification. We propose to use Block Ridgelet Transform (BRT)...
This paper proposes a new ridgelet transform-based method to detect spoof fingerprint attacks in fingerprint biometric systems. It uses differences in textural characteristics observed in real and spoof fingerprints for spoof detection. Textural measures based on ridgelet energy signatures and ridgelet co-occurrence signatures are used to characterize fingerprint texture. Principal component analysis...
This paper proposes a new curvelet transform-based method to detect spoof fingerprint attacks in fingerprint biometric systems. It uses only one image to differentiate a real fingerprint from a spoof one. It is based on the observation that, real and spoof fingerprints exhibit different textural characteristics. Textural measures based on curvelet energy signatures and curvelet co-occurrence signatures...
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