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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 texture-based method to spoof-proof a fingerprint biometric system. The fundamental basis of this anti-spoofing method is that, real fingerprint exhibits different textural characteristics from a spoof one. Textural measures based on wavelet energy signatures and gray level co-occurrence matrix (GLCM) features are used to characterize fingerprint texture. Dimensionalities of...
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...
This paper describes an image-based system to detect spoof fingerprint attacks in fingerprint biometric systems. It is based on the observation that, real and spoof fingerprints exhibit different textural characteristics. These are based on structural, orientation, roughness, smoothness and regularity differences of diverse regions in a fingerprint image. Local binary pattern (LBP) histograms are...
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