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International Workshop on Digital Watermarking

IWDW 2013: Digital-Forensics and Watermarking pp 314–325Cite as

A Distributed Scheme for Image Splicing Detection

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8389))

Abstract

In order to capture more splicing traces and to improve the robustness to anti-forensics, combining different kinds of features are adopted for image detection work in recently years. However, the combined features inevitably increase the feature dimensionality and the computational complexity. In this paper, we propose a distributed approach to reducing the computational complexity introduced by the high-dimensional features in image splicing detection. We introduce first-order noncausal model to the splicing detection work and give the distributed solution to this model. The noncausal model is split into several small tasks which are solved simultaneously by the distributed scheme. Experimental results over the public Columbia Image Splicing Detection Evaluation Dataset show that the distributed noncausal model could differentiate between splicing images and natural ones effectively.

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References

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Acknowledgements

This research work is funded by the National Science Foundation of China (61271316,61071152), 973 Programs (2010CB731403, 2010CB731406) of China and National “Twelfth Five-Year” Plan for Science & Technology Support (2012BAH38B04). Credits for the use of the Columbia Image Splicing Detection Evaluation Dataset are given to the DVMM Laboratory of Columbia University, CalPhotos Digital Library and the photographers listed in http://www.ee.columbia.edu/ln/dvmm/downloads/AuthSplicedDataSet/photographers.htm.

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Authors and Affiliations

  1. Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China

    Xudong Zhao, Shenghong Li & Jianhua Li

  2. School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, 200240, People’s Republic of China

    Shilin Wang & Xiang Lin

Authors
  1. Xudong Zhao
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  2. Shilin Wang
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  3. Shenghong Li
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  4. Jianhua Li
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  5. Xiang Lin
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Corresponding author

Correspondence to Xudong Zhao .

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Editors and Affiliations

  1. New Jersey Institute of Technology, Newark, New Jersey, USA

    Yun Qing Shi

  2. CIST, Korea University, Seoul, Korea, Republic of (South Korea)

    Hyoung-Joong Kim

  3. EE Telecomunicacion, University of Vigo, Vigo, Spain

    Fernando Pérez-González

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© 2014 Springer-Verlag Berlin Heidelberg

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Zhao, X., Wang, S., Li, S., Li, J., Lin, X. (2014). A Distributed Scheme for Image Splicing Detection. In: Shi, Y., Kim, HJ., Pérez-González, F. (eds) Digital-Forensics and Watermarking. IWDW 2013. Lecture Notes in Computer Science(), vol 8389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43886-2_23

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  • DOI: https://doi.org/10.1007/978-3-662-43886-2_23

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43885-5

  • Online ISBN: 978-3-662-43886-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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