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Image-Based Object Spoofing Detection

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11255))

Abstract

Using 2D images in authentication systems raises the question of spoof attacks: is it possible to deceive an authentication system using fake models possessing identical visual properties of the genuine one? In this work, an anti-spoofing method approach for a wine anti-counterfeiting system is presented. The proposed method relies in two different color spaces: CIE L*u*v* and \(YC_rC_b\), to distinguish between a genuine instance and a spoof attack. To evaluate the proposed strategy, two databases were used: a private database, with photos/2D attacks of cork stoppers, created for this work; and the public Replay-Attack database that is used for face spoofing detection methods testing. The results on the private database show that the anti-spoofing approach is able to distinguish with high accuracy a real photo from an attack. Regarding the public database, the results were obtained with existing methods, as the best HTER results using a single frame approach.

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Notes

  1. 1.

    The source code of this work is available at: https://github.com/ee09115/spoofing_detection.

  2. 2.

    https://opencv.org/.

  3. 3.

    http://scikit-learn.org/stable/index.html.

  4. 4.

    https://www.idiap.ch/dataset/replayattack.

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Acknowledgments

Authors gratefully acknowledge the funding of Project NORTE-01-0145-FEDER-000022 - SciTech - Science and Technology for Competitive and Sustainable Industries, co-financed by Programa Operacional Regional do Norte (NORTE2020), through Fundo Europeu de Desenvolvimento Regional (FEDER).

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Correspondence to Valter Costa .

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Costa, V., Sousa, A., Reis, A. (2018). Image-Based Object Spoofing Detection. In: Barneva, R., Brimkov, V., Tavares, J. (eds) Combinatorial Image Analysis. IWCIA 2018. Lecture Notes in Computer Science(), vol 11255. Springer, Cham. https://doi.org/10.1007/978-3-030-05288-1_15

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