Abstract
This work introduces a new approach to fake finger detection, based on the analysis of human skin elasticity. When a user puts a finger on the scanner surface, a sequence of fingerprint images which describes the finger deformation process is captured. Then two features which represent the skin elasticity are extracted from the image sequence: 1) the correlation coefficient of the fingerprint area and the signal intensity; 2) the standard deviation of the fingerprint area extension in x and y axes. Finally the Fisher Linear Discriminant is used to discriminate the finger skin from other materials such as gelatin. The experiments carried out on a dataset of real and fake fingers show that the proposed approach and features are effective in fake finger detection.
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Jia, J., Cai, L., Zhang, K., Chen, D. (2007). A New Approach to Fake Finger Detection Based on Skin Elasticity Analysis. In: Lee, SW., Li, S.Z. (eds) Advances in Biometrics. ICB 2007. Lecture Notes in Computer Science, vol 4642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74549-5_33
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DOI: https://doi.org/10.1007/978-3-540-74549-5_33
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