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Image-Based Object Spoofing Detection

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Combinatorial Image Analysis (IWCIA 2018)

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

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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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Authors and Affiliations

  1. FEUP - Faculty of Engineering of the University of Porto, Rua Dr. Roberto Frias s/n Porto, Porto, Portugal

    Valter Costa, Armando Sousa & Ana Reis

  2. INEGI - Institute of Science and Innovation in Mechanical and Industrial Engineering, Campus da FEUP, Rua Dr. Roberto Frias 400 Porto, Porto, Portugal

    Valter Costa & Ana Reis

  3. INESC TEC - INESC Technology and Science (formerly INESC Porto), Campus da FEUP, Rua Dr. Roberto Frias Edifício I, Porto, Portugal

    Armando Sousa

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  1. Valter Costa
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  2. Armando Sousa
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Correspondence to Valter Costa .

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Editors and Affiliations

  1. State University of New York at Fredonia, Fredonia, NY, USA

    Reneta P. Barneva

  2. State University of New York, Buffalo, NY, USA

    Valentin E. Brimkov

  3. University of Porto, Porto, Portugal

    João Manuel R.S. Tavares

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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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