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A robust detection algorithm for copy-move forgery in digital images

A robust detection algorithm for copy-move forgery in digital images. 1. Source : Forensic Science International, Volume 214, Issues 1–3, 10 January 2012 Authors : Yanjun Cao , Tiegang Gao , Li Fan , Qunting Yang Presenter : Li-Ting Liao Date : 2012/06/14. OUTLINE. 2.

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A robust detection algorithm for copy-move forgery in digital images

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  1. A robust detection algorithm for copy-move forgery in digital images 1 Source: Forensic Science International, Volume 214, Issues 1–3, 10 January 2012 Authors: Yanjun Cao, Tiegang Gao, Li Fan, Qunting Yang Presenter: Li-Ting Liao Date: 2012/06/14

  2. OUTLINE 2 • Introduction • Proposed Scheme • Experimental Results • Conclusions

  3. Copy-move forgery Original image Tamper image detect Introduction 3

  4. Flowchart of the proposed scheme Proposed Scheme 4

  5. B B B B N N THE PROPOSED SCHEME – Block Dividing (1/2) 5 Generate (N-B+1)(N-B+1) Blocks

  6. THE PROPOSED SCHEME –Block Dividing (2/2) 6 Block size : 4 × 4 … Original image

  7. DCT Transform THE PROPOSED SCHEME – DCT transform 7 DCT coefficient block Original block

  8. Generate matching feature ： C1 C2 C4 C3 THE PROPOSED SCHEME – Feature extraction (1/2) 8 DCT coefficient block

  9. C1 C2 ≒ 145.2746 C4 C3 ≒ 0.8715 ≒ -0.0095 ≒ -0.7716 THE PROPOSED SCHEME – Feature extraction (2/2) 9 Generate matching feature ： DCT coefficient block

  10. Similar condition ： (x1, y1) 1 2X2 (x2, y2) d 2 2X2 THE PROPOSED SCHEME – Matching (1/3) 10

  11. Not Similar THE PROPOSED SCHEME – Matching (2/3) 11

  12. ≒ 127.28 Similar Detected image THE PROPOSED SCHEME – Matching (3/3) 12

  13. EXPERIMENTAL RESULTS(1/6) 13 The detection results (from left to right is the original image, tampered image, detection results).

  14. EXPERIMENTAL RESULTS(2/6) 14 The detection results for non-regular copy-move forgery

  15. EXPERIMENTAL RESULTS(3/6) 15 The test results for multiple copy-move forgery under a mixed operation

  16. EXPERIMENTAL RESULTS(4/6) 16 The top row are tampered images with duplicated region size of 32 pixels × 32 pixels. Shown below are the detection results using our algorithm

  17. (a) (b) EXPERIMENTAL RESULTS(5/6) 17 DAR curves for DCT, DCT-improved, PCA, FMT, and Proposed methods when the duplicated region is 64 pixels 64 pixels. (a) Gaussian noise, and (b) Gaussian blurring

  18. EXPERIMENTAL RESULTS(6/6) 18 [2] A. Fridrich, et al., Detection of Copy-move Forgery in Digital Images, 2003. [3] Y. Huang, et al., Improved DCT-based detection of copy-move forgery in images, Forensic Science International 206 (1–3) (2011) 178–184. [4] A. Popescu and H. Farid, Exposing digital forgeries by detecting duplicated image regions, Dept. Comput. Sci., Dartmouth College, Tech. Rep. TR2004-515, 2004.

  19. CONCLUSIONS 19 • This paper presented an automatic and efficient detection algorithm for copy-move forgery • The proposed algorithm could not only endure the multiple copy-move forgery, but also the blurring or nosing adding

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