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Efficient image splicing detection algorithm based on markov features

  • Nam Thanh Pham
  • Jong-Weon Lee
  • Goo-Rak Kwon
  • Chun-Su ParkEmail author
Article
  • 83 Downloads

Abstract

Image splicing is one of the most common methods for digital image tampering. In this paper, an efficient Markov features based algorithm is proposed for image splicing detection. The proposed algorithm first extracts two types of Markov features, coefficient-wise Markov features and block-wise Markov features in the discrete cosine transform (DCT) domain. The former are obtained by exploiting correlations between consecutive coefficients and the latter are computed by exploiting coefficient correlations between adjacent blocks. Then, a feature vector is obtained by combining these two Markov features and it is fed into support vector machine (SVM) for the classification of authentic and spliced images. The experimental results show that the proposed method not only achieves much higher detection accuracy but also reduces the total running time significantly in comparison with state-of-the-art methods.

Keywords

Image splicing Markov features DCT domain Support vector machine 

Notes

Acknowledgements

This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2017-2016-0-00312) supervised by the IITP (Institute for Information & communications Technology Promotion). This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2016R1C1B1009682).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Nam Thanh Pham
    • 1
  • Jong-Weon Lee
    • 2
  • Goo-Rak Kwon
    • 3
  • Chun-Su Park
    • 4
    Email author
  1. 1.Department of Digital ContentsSejong UniversitySeoulSouth Korea
  2. 2.Department of SoftwareSejong UniversitySeoulSouth Korea
  3. 3.Department of Information and Communication EngineeringChosun UniversityDongguSouth Korea
  4. 4.Department of Computer EducationSungkyunkwan UniversitySeoulSouth Korea

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