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Abstract

Copy-move forgery is one of the famous manipulation technique in digital image. Many block-based techniques have been proposed previously for forgery detection, but most of them have higher computational complexity due to higher number of feature vectors dimension. In this paper, we have tried to reduce the feature vectors dimension. This paper proposes a copy-move forgery detection (CMFD) technique based on circular blocks and discrete cosine transform (DCT) with fewer feature vectors than the prevalent methods. Initially an input image is taken and divided into overlapping blocks. To extract the features from each block, DCT transformation is used on each block. Then, these features are represented using a circle block to reduce the feature vectors dimension. The extracted feature vectors are then used for matching process to locate the manipulated regions. Experimental results depict the performance of the proposed method and robustness against the post-processing operations. The computational complexity of the proposed method is lower than the existing techniques due to fewer feature vectors dimension.

Keywords

Forensic science image forensic forensics photography regionduplication detection copy-move forgery.

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References

, –http://www.fourandsix.com/photo-tampering-history/tag/science.

Christlein

, Jordan

, Riess

and Angelopoulou

, An evaluation of popular copy- move forgery detection approaches, IEEE Transactions on Information Forensics and Security7(6) (2012), 1841–1854.

Fridrich

, Lukas

and Soukal

, Detection of copy-move forgery in digital images, In Proceedings of Digital Forensic Research Workshop, Citeseer, 2003.

Huang

, Sun

, Lu

and Long

, Improved DCT-based detection of copy-move forgery in images, Forensic Science International, Elsevier206(1) (2011), 178–184.

Popescu

A.C.

and Farid

, Exposing digital forgeries by detecting duplicated image region [Technical Report], 2004-515, Hanover, Department of Computer Science, Dartmouth College, USA, 2004.

Luo

, Huang

and Qiu

, Robust detection of region-duplication forgery in digital image, In 18th International Conference on Pattern Recognition, IEEE4 (2006), 746–749.

Mahdian

and Saic

, Detection of copy-move forgery using a method based on blur moment invariants, Forensic Science International, Elsevier171(2) (2007), 180–189.

Bayram

, Memon

and Sencar Acoustics

H.T.

, An efficient and robust method for detecting copy-move forgery, IEEE (2009), pp. 1053–1056.

Pan

and Lyu

, Detecting image region duplication using SIFT features, IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP) (2010), pp. 1706–1709.

10.

Alkawaz

T.S.

, Hazim

, Sulong

and Rehman

, Detection of copy-move image forgery based on discrete cosine transform, Neural Computing and Applications (2016), pp. 1–10.

11.

Zhong

, Huang

, Young

, Gan

and Lin

, A new block-based method for copy move forgery detection under image geometric transforms, Multimedia Tools and Applications76(13) (2017), pp. 14887–14903.

12.

Wang

, Shi

and Wang

, An Efficient Passive Authentication Scheme for Copy-Move Forgery Based on DCT, Springer International Publishing, In International Conference on Cloud Computing and Security (2016), pp. 417–429.

13.

Cao

, Gao

, Yang

, Fan

and Gao

, A robust detection algorithm for copy-move forgery in digital images, Forensic Science International214(1) (2012), 33–43.

14.

Luo

, Qiu

and Huang

, Robust detection of region-duplication forgery in digital image, In 18th Inter- national Conference on Pattern Recognition (ICPR’06)4 (2006), pp. 746–749.

15.

Khizar

and Qazi

, Forgery detection in digital images via discrete wavelet and discrete cosine transforms, Computers & Electrical Engineering, 2017.

16.

Kang

XB.

and Wei

SM.

, Identifying tampered regions using singular value decomposition in digital image forensics, International Conference on Computer Science and Software Engineering3 (2008), 926–930.

17.

Bayram

, Memon

and Sencar

H.T.

, An efficient and robust method for detecting copy-move forgery, In 2009 IEEE International Conference on Acoustics, Speech and Signal Processing (2009), pp. 1053–1056.

18.

, Zhu

, Li

, Chu

S-C.

, Pan

J-S.

and Roddick

J.F.

, An efficient scheme for detecting copy-move forged images by local binary patterns, Journal of Information Hiding and Multimedia Signal Processing4(1) (2013), pp. 46–56.

19.

Lin

H-J.

, Kao

Y-T.

and Wang

C-W.

, Fast copy-move forgery detection, WSEAS Transactions on Signal Processing5(5) (2009), 188–197.

20.

Yang

, Zhang

and Yang

, Rotation In-variant Local Binary Pattern for Blind Detection of Copy- Move Forgery with Affine Transform, In International Conference on Cloud Computing and Security, Springer International Publishing (2016), pp. 404–416.

Detection of copy-move image forgery with efficient block representation and discrete cosine transform

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