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Detecting Copy-move Forgeries in Images Based on DCT and Main Transfer Vectors

  • Zhang, Zhi (School of Mechanical, Electrical and Information Engineering, Shandong University) ;
  • Wang, Dongyan (School of Mechanical, Electrical and Information Engineering, Shandong University) ;
  • Wang, Chengyou (School of Mechanical, Electrical and Information Engineering, Shandong University) ;
  • Zhou, Xiao (School of Mechanical, Electrical and Information Engineering, Shandong University)
  • Received : 2017.01.23
  • Accepted : 2017.05.26
  • Published : 2017.09.30

Abstract

With the growth of the Internet and the extensive applications of image editing software, it has become easier to manipulate digital images without leaving obvious traces. Copy-move is one of the most common techniques for image forgery. Image blind forensics is an effective technique for detecting tampered images. This paper proposes an improved copy-move forgery detection method based on the discrete cosine transform (DCT). The quantized DCT coefficients, which are feature representations of image blocks, are truncated using a truncation factor to reduce the feature dimensions. A method for judging whether two image blocks are similar is proposed to improve the accuracy of similarity judgments. The main transfer vectors whose frequencies exceed a threshold are found to locate the copied and pasted regions in forged images. Several experiments are conducted to test the practicability of the proposed algorithm using images from copy-move databases and to evaluate its robustness against post-processing methods such as additive white Gaussian noise (AWGN), Gaussian blurring, and JPEG compression. The results of experiments show that the proposed scheme effectively detects both copied region and pasted region of forged images and that it is robust to the post-processing methods mentioned above.

Keywords

References

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