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Statistical anti-spoofing method for fingerprint recognition

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Abstract

Recently, attempts at spoofing biometric fingerprint recognition systems through fake fingerprints have been frequently reported. Most existing fake fingerprint detection methods require either additional sensors or complicated calculations. In this paper, a fake fingerprint detection method is proposed that employs combinations of six simple statistical moment features. These features are deviation, variance, skewness, kurtosis, hyperskewness, and hyperflatness of the fingerprints. In addition, the average brightness, standard deviation, and differential features are considered. Of all features, the best ones are selected in terms of the overlap ratio between real and fake fingerprint images. The multi-dimensional features are combined at the feature level through a support vector machine. Based on the experimental results, the proposed method showed classification accuracy of approximately 99%.

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Acknowledgements

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-R0992-16-1014) supervised by the IITP (Institute for Information & communications Technology Promotion). This research was also supported by the Bio & Medical Technology Development Program of the NRF funded by the Korean government, MSIP (2016M3A9E1915855). The funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

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Authors and Affiliations

  1. Department of Computer Science, Sangmyung University, Hongjimun 2-Gil 20, Jongno-Gu Seoul, 03016, Republic of Korea

    Yosep Park & Unsoo Jang

  2. Department of Intelligent Engineering Informatics for Human, Sangmyung University, Hongjimun 2-Gil 20, Jongno-Gu Seoul, 03016, Republic of Korea

    Eui Chul Lee

Authors
  1. Yosep Park
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  2. Unsoo Jang
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  3. Eui Chul Lee
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Correspondence to Eui Chul Lee.

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The authors declare that there is no conflict of interest.

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Communicated by J. Park.

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Park, Y., Jang, U. & Lee, E.C. Statistical anti-spoofing method for fingerprint recognition. Soft Comput 22, 4175–4184 (2018). https://doi.org/10.1007/s00500-017-2707-3

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  • DOI: https://doi.org/10.1007/s00500-017-2707-3

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