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Image Fakery and Neural Network Based Detection

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

By right of the great convenience of computer graphics and digital imaging, it is much easier to alter the content of an image than before without any visually traces. Human has not believed what they see. Many digital images can not be judged whether they are real or feigned visually, i.e., many fake images are produced whose content is feigned. In this paper, firstly, image fakery is introduced, including how to produce fake images and its characters. Then, a fake image detection scheme is proposed, which uses radial basis function (RBF) neural network as a detector to make a binary decision on whether an image is fake or real. The experimental results also demonstrated the effectiveness of the proposed scheme.

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References

  1. Popescu, A.C., Farid, H.: Exposing Digital Forgeries by Detecting Traces of Resampling. IEEE Transactions on Signal Processing 53, 758–767 (2005)

    Article  Google Scholar 

  2. Popescu, A., Farid, H.: Statistical Tools for Digital Forensics. In: Fridrich, J. (ed.) IH 2004. LNCS, vol. 3200, pp. 128–147. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  3. Ng, T.T., Chang, S.F.: A Model for Image Splicing. In: IEEE Int. Conf. on Image Processing (ICIP), vol. 2, pp. 1169–1172 (2004)

    Google Scholar 

  4. Ng, T.T., Chang, S.F., Sun, Q.: Blind Detection of Photomontage Using Higher Order Statistics. In: IEEE Int. Symposium on Circuits and Systems (ISCAS), vol. 5, pp. 688–691 (2004)

    Google Scholar 

  5. Lu, H., Shen, R., Chung, F.L.: Fragile Watermarking Scheme for Image Authentication. Electronics Letters 39, 898–900 (2003)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China

    Wei Lu & Hongtao Lu

  2. Department of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China

    Wei Lu & Fu-Lai Chung

Authors
  1. Wei Lu
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  2. Fu-Lai Chung
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  3. Hongtao Lu
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Lu, W., Chung, FL., Lu, H. (2006). Image Fakery and Neural Network Based Detection. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_90

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  • DOI: https://doi.org/10.1007/11760023_90

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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