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Document Forgery Detection with SVM Classifier and Image Quality Measures

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Advances in Multimedia Information Processing - PCM 2008 (PCM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5353))

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Abstract

This paper presents a detection scheme for a fraudulent document made by printers. The fraud document is indistinguishable by the naked eye from a genuine document because of the technological advances in printing methods. Even though we cannot find any visual evidence of forgery, the fraud document includes inherent device features. We propose a method to uncover these features. 17 image quality measures are applied to discriminate between genuine and fake documents. The results of each measure are used as training and testing parameters of SVM classifier to determine fake documents. Preliminary experimental results are presented based on the fraud gift voucher made by several color printers.

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Author information

Authors and Affiliations

  1. Department of EECS, Korea Advanced Institute of Science and Technology Guseong-dong, Yuseong-gu, Daejeon, Republic of Korea

    Seung-Jin Ryu & Heung-Kyu Lee

  2. School of Computer and Software Engineering, Kumoh National Institute of Technology, Yangho-dong, Gumi, Gyeongbuk, Republic of Korea

    Hae-Yeoun Lee

  3. Anti-counterfeit Center, Technology Research Institute, Korea Minting & Security Printing Corporation, 35 Gajeong-dong, Yuseong-gu, Daejeon, Republic of Korea

    Il-Weon Cho

Authors
  1. Seung-Jin Ryu
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  2. Hae-Yeoun Lee
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  3. Il-Weon Cho
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  4. Heung-Kyu Lee
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Editor information

Editors and Affiliations

  1. Department of Engineering Science, National Cheng Kung University, No.1, University Road, 701, Tainan City, Taiwan

    Yueh-Min Ray Huang

  2. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95, Zhongguancun East Road, 100190, Beijing, China

    Changsheng Xu

  3. Institute of Biomedical Engineering, National Cheng Kung University, No. 1, University Road, 701, Tainan City, Taiwan

    Kuo-Sheng Cheng

  4. Department of Electrical Engineering, National Cheng Kung University, No. 1, University Road, 701, Tainan City, Taiwan

    Jar-Ferr Kevin Yang

  5. Department of Electrical and Computer Engineering, Concordia University, S-EV005.139, 1515 St. Catherine West, Montreal, H4G 2W1, Quebec, Canada

    M. N. S. Swamy

  6. Microsoft Research Asia, 5/F, Beijing Sigma Center, No. 49, Zhichun Road, Hai Dian District, 100080, Beijing, China

    Shipeng Li

  7. Department of Information Management, National Kaohsiung University of Applied Sciences, No. 415, Jiangong Road, Sanmin District, 80778, Kaohsiung, Taiwan

    Jen-Wen Ding

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© 2008 Springer-Verlag Berlin Heidelberg

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Ryu, SJ., Lee, HY., Cho, IW., Lee, HK. (2008). Document Forgery Detection with SVM Classifier and Image Quality Measures. In: Huang, YM.R., et al. Advances in Multimedia Information Processing - PCM 2008. PCM 2008. Lecture Notes in Computer Science, vol 5353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89796-5_50

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  • DOI: https://doi.org/10.1007/978-3-540-89796-5_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89795-8

  • Online ISBN: 978-3-540-89796-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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