1. 1 A robust detection algorithm for copy- move forgery in digital images 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. Introduction 3 Original imageTamper image Copy-move forgery detect

4. Proposed Scheme 4 Flowchart of the proposed scheme

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

6. THE PROPOSED SCHEME –Block Dividing (2/2) 6 155 158 156158159 155 158 156158159 155 158 156158159 155 158 156158159 155 158 156158159 151 154157156 155 156157158156153 149 153155154153154 Original image 155 158 155 158 155 158 155 158 155 158 155 158 155 158 155 158 … 156158159 157156 157158156153 155154153154 Block size : 4 × 4

7. THE PROPOSED SCHEME – DCT transform 7 155 158 155 158 155 158 155 158 420.7537.70297-3.254.136577 -2.986190.9267772.1744-0.32322 -0.25-5.440810.75-0.72292 2.5899120.676777-0.630070.573223 DCT Transform Original block DCT coefficient block

8. THE PROPOSED SCHEME – Feature extraction (1/2) 8 420.7537.70297-3.254.136577 -2.986190.9267772.1744-0.32322 -0.25-5.440810.75-0.72292 2.5899120.676777-0.630070.573223 DCT coefficient block C2C1 C3C4 Generate matching feature ：

9. THE PROPOSED SCHEME – Feature extraction (2/2) 9 420.7537.70297-3.254.136577 -2.986190.9267772.1744-0.32322 -0.25-5.440810.75-0.72292 2.5899120.676777-0.630070.573223 DCT coefficient block C2C1 C3C4 Generate matching feature ： ≒ 145.2746 ≒ 0.8715 ≒ -0.7716 ≒ -0.0095

10. THE PROPOSED SCHEME – Matching (1/3) 10 d 1 2X2 2 (x 1, y 1 ) (x 2, y 2 ) Similar condition ：

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

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

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. 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 (a) (b)

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 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 19