article

Fast copy-move forgery detection

Authors:

Yang-Ta KaoAuthors Info & Claims

WSEAS Transactions on Signal Processing, Volume 5, Issue 5

Pages 188 - 197

Published: 01 May 2009 Publication History

Abstract

This paper proposes a method for detecting copy-move forgery over images tampered by copy-move. To detect such forgeries, the given image is divided into overlapping blocks of equal size, feature for each block is then extracted and represented as a vector, all the extracted feature vectors are then sorted using the radix sort. The difference (shift vector) of the positions of every pair of adjacent feature vectors in the sorting list is computed. The accumulated number of each of the shift vectors is evaluated. A large accumulated number is considered as possible presence of a duplicated region, and thus all the feature vectors corresponding to the shift vectors with large accumulated numbers are detected, whose corresponding blocks are then marked to form a tentative detected result. Finally, the medium filtering and connected component analysis are performed on the tentative detected result to obtain the final result. Compared with other methods, employing the radix sort makes the detection much more efficient without degradation of detection quality.

References

[1]

C. T. Hsieh and Y. K. Wu, "Geometric Invariant Semi-fragile Image Watermarking Using Real Symmetric Matrix," WSEAS Transaction on Signal Processing, Vol. 2, Issue 5, May 2006, pp. 612-618.

[2]

C. T. Hsieh, Y. K. Wu, and K. M. Hung, "An Adaptive Image Watermarking System Using Complementary Quantization," WSEAS Transaction on Information Science and Applications, Vol. 3, Issue 12, 2006, pp. 2392-2397.

[3]

K. M. Hung, C. T. Hsieh and Y. K. Wu, "Multi-Purpose Watermarking Schemes for Color Halftone Image Based on Wavelet and Zernike Transform," WSEAS Transaction on Computer, Vol. 6, Issue 1, 2007, pp. 9-14.

[4]

F. Hartung and M. Kutter, "Multimedia Watermarking Techniques," in Proceedings of the IEEE, Vol. 87, No. 7, July 1999, pp. 1079-1107.

[5]

P. Meerwald and A. Uhl, "A Survey of Wavelet-Domain Watermarking Algorithms," in Proceedings of SPIE, Electronic Imaging, Security and Watermarking of Multimedia Contents, Vol. 4314, 2001, pp. 505-516.

[6]

W. Lu, F. L. Chung, and H. Lu, "Blind Fake Image Detection Scheme Using SVD," IEICE Transaction on Communications, Vol. E89-B, No. 5, May 2006, pp. 1726-1728.

[7]

M. S. Wang and W. C. Chen, "A Majority-Voting based Watermarking Scheme for Color Image Tamper Detection and Recovery", Computer Standards & Interfaces, Vol. 29, Issue 5, 2007, pp. 561-570.

Digital Library

[8]

P. L. Lin, C. K. Hsieh, and P. W. Huang, "A Hierarchical Digital Watermarking Method for Image Tamper Detection and Recovery, Pattern Recognition, Vol. 38, Issue 12, 2005, pp. 2519-2529.

Digital Library

[9]

K. F. Li, T. S. Chen, and S. C. Wu, "Image Tamper Detection and Recovery System Based on Discrete Wavelet Transformation," International Conference Communications, Computers and Signal Processing, Vol. 1, 2001, pp. 26-28.

[10]

A. C. Popescu and H. Farid, "Exposing Digital Forgeries by Detecting Traces of Resampling," IEEE Transactions on Signal Processing, Vol. 53, 2005, pp. 758-767.

Digital Library

[11]

E. S. Gopi, N. Lakshmanan, T. Gokul, S. KumaraGanesh, and P. R. Shah, "Digital Image Forgery Detection using Artificial Neural Network and Auto Regressive Coefficients," Electrical and Computer Engineering, 2006, pp. 194-197.

[12]

M. K. Johnson and H. Farid, "Exposing Digital Forgeries by Detecting Inconsistencies in Lighting," in Proceedings of ACM Multimedia and Security Workshop, New York, 2005, pp. 1-9.

[13]

R. Brunelli, "Estimation of Pose and Illuminant Direction for Face Processing," Image and Vision Computing, Vol. 15, No. 10, October 1997, pp. 741-748.

[14]

A. P. Pentland, "Finding the illuminant direction," Journal of the Optical Society of America, Vol. 72, Issue 4, 1982, pp. 448-455.

[15]

W. Zhou and C. Kambhamettu, "Estimation of Illuminant Direction and Intensity of Multiple Light Sources," in Proceedings of the 7th European Conference on Computer Vision-Part IV, 2002, pp. 206-220.

[16]

P. Nillius and J. O. Eklundh, "Automatic Estimation of the Projected Light Source Direction," in Proceedings of 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 1, 2001, pp. 1076-1083.

[17]

T. E. Boult and G. Wolberg, "Correcting Chromatic Aberrations Using Image Warping," in Proceedings of Computer Vision and Pattern Recognition, 1992, pp. 684-687.

[18]

M. K. Johnson and H. Farid, "Exposing Digital Forgeries Through Chromatic Aberration," in Proceedings of the 8th workshop on Multimedia and security, 2006, pp. 48-55.

[19]

J. Lukas, J. Fridich, and M. Goljan, "Detecting Digital Image Forgeries Using Sensor Pattern Noise," in Proceedings of the SPIE Conference on Security, Steganography, and Watermarking of Multimedia Contents, Vol. 6072, January 2006, pp. 362-372.

[20]

N. Khanna, A. K. Mikkilineni, G. T. C. Chiu, J. P. Allebach, and E. J. Delp, "Scanner Identification Using Sensor Pattern Noise," in Proceedings of the SPIE International Conference on Security, Steganography, and Watermarking of Multimedia Contents IX, Vol. 6505, No. 1, 2007, pp. 65051K.

[21]

J. Lukas, J. Fridrich, and M. Goljan, "Determining Digital Image Origin Using Sensor Imperfections," in Proceedings of SPIE Electronic Imaging, Image and Video Communication and Processing, January 16-20, 2005, pp. 249-260.

[22]

A. C. Popescu and H. Farid, "Exposing Digital Forgeries in Color Filter Array Interpolated Images," IEEE Transactions on Signal Processing, Vol. 53, 2005, pp. 3948-3959.

Digital Library

[23]

J. Fridrich, D. Soukal, and J. Lukas, "Detection of Copy-Move Forgery in Digital Images," in Proceedings of Digital Forensic Research Workshop, August 2003.

[24]

A. C. Popescu and H. Farid, "Exposing Digital Forgeries by Detecting Duplicated Image Regions," Technical Report, TR2004-515, Department of Computer Science, Dartmouth College, 2004.

[25]

G. Li, Q. Wu, D. Tu, and S. Sun, "A Sorted Neighborhood Approach for Detecting Duplicated Regions in Image Forgeries based on DWT and SVD," in Proceedings of IEEE International Conference on Multimedia and Expo, Beijing China, July 2-5, 2007, pp. 1750-1753.

[26]

W. Luo, J. Huang, and G. Qiu, "Robust Detection of Region Duplication Forgery in Digital Image," in Proceedings of the 18th International Conference on Pattern Recognition, Vol. 4, 2006, pp. 746-749.

[27]

A. N. Myna, M. G. Venkateshmurthy, and C. G. Patil, "Detection of Region Duplication Forgery in Digital Images Using Wavelets and Log-Polar Mapping," in Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007), Vol. 3, 2007, pp. 371-377.

[28]

H. Huang, W. Guo, and Y. Zhang, "Detection of Copy-Move Forgery in Digital Images Using SIFT Algorithm," in Proceedings of IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, Vol. 2, 2008, pp. 272-276.

Digital Library

Cited By

Capasso PCattaneo GDe Marsico M(2024)A Comprehensive Survey on Methods for Image IntegrityACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363320320:11(1-34)Online publication date: 12-Sep-2024
https://dl.acm.org/doi/10.1145/3633203
Monika Bansal DPassi A(2022)Image Forgery Detection and Localization Using Block Based and Key-Point Based Feature Matching Forensic InvestigationWireless Personal Communications: An International Journal10.1007/s11277-022-09898-2127:4(2823-2839)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s11277-022-09898-2
Jaiswal ASrivastava R(2022)Detection of Copy-Move Forgery in Digital Image Using Multi-scale, Multi-stage Deep Learning ModelNeural Processing Letters10.1007/s11063-021-10620-954:1(75-100)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s11063-021-10620-9
Show More Cited By

Fast copy-move forgery detection
1. Theory of computation
  1. Design and analysis of algorithms
    1. Data structures design and analysis

Recommendations

Copy-move forgery detection

The authenticity and reliability of digital images are increasingly important due to the ease in modifying such images. Thus, the capability to identify image manipulation is a current research focus, and a key domain in digital image authentication is ...
An Image Copy Move Forgery Detection Method Using QDCT
ICIMCS'16: Proceedings of the International Conference on Internet Multimedia Computing and Service

With a rapid evolution of computer science, digital image manipulation becomes much more easily. One of the most commonly tampering with a digital image is copy-move forgery, in which a part of image is copied and used to cover another part in a ...
Detection of copy-rotate-move forgery using Zernike moments
IH'10: Proceedings of the 12th international conference on Information hiding

As forgeries have become popular, the importance of forgery detection is much increased. Copy-move forgery, one of the most commonly used methods, copies a part of the image and pastes it into another part of the the image. In this paper, we propose a ...

Comments

Information & Contributors

Information

Published In

cover image WSEAS Transactions on Signal Processing

WSEAS Transactions on Signal Processing Volume 5, Issue 5

May 2009

41 pages

ISSN:1790-5052

EISSN:2224-3488

Issue’s Table of Contents

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Stevens Point, Wisconsin, United States

Publication History

Published: 01 May 2009

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

32
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 13 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Capasso PCattaneo GDe Marsico M(2024)A Comprehensive Survey on Methods for Image IntegrityACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363320320:11(1-34)Online publication date: 12-Sep-2024
https://dl.acm.org/doi/10.1145/3633203
Monika Bansal DPassi A(2022)Image Forgery Detection and Localization Using Block Based and Key-Point Based Feature Matching Forensic InvestigationWireless Personal Communications: An International Journal10.1007/s11277-022-09898-2127:4(2823-2839)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s11277-022-09898-2
Jaiswal ASrivastava R(2022)Detection of Copy-Move Forgery in Digital Image Using Multi-scale, Multi-stage Deep Learning ModelNeural Processing Letters10.1007/s11063-021-10620-954:1(75-100)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s11063-021-10620-9
Chennamma HMadhushree B(2022)A comprehensive survey on image authentication for tamper detection with localizationMultimedia Tools and Applications10.1007/s11042-022-13312-182:2(1873-1904)Online publication date: 14-Jun-2022
https://dl.acm.org/doi/10.1007/s11042-022-13312-1
Kaur GSingh NKumar M(2022)Image forgery techniques: a reviewArtificial Intelligence Review10.1007/s10462-022-10211-756:2(1577-1625)Online publication date: 6-Jun-2022
https://dl.acm.org/doi/10.1007/s10462-022-10211-7
Huynh KLy TNguyen P(2021)Improving the Accuracy in Copy-Move Image Detection: A Model of Sharpness and BlurrinessSN Computer Science10.1007/s42979-021-00682-w2:4Online publication date: 19-May-2021
https://dl.acm.org/doi/10.1007/s42979-021-00682-w
Monika Bansal DPassi A(2021)Image Forensic Investigation Using Discrete Cosine Transform-Based ApproachWireless Personal Communications: An International Journal10.1007/s11277-021-08396-1119:4(3241-3253)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s11277-021-08396-1
Dixit ABag S(2020)Utilization of edge operators for localization of copy-move image forgery using WLD-HOG features with connected component labelingMultimedia Tools and Applications10.1007/s11042-020-09230-979:35-36(26061-26097)Online publication date: 1-Sep-2020
https://dl.acm.org/doi/10.1007/s11042-020-09230-9
Ouyang JLiu YLiao M(2019)Robust copy-move forgery detection method using pyramid model and Zernike momentsMultimedia Tools and Applications10.1007/s11042-018-6605-178:8(10207-10225)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s11042-018-6605-1
Chen BYu MSu QLi L(2019)Fractional quaternion cosine transform and its application in color image copy-move forgery detectionMultimedia Tools and Applications10.1007/s11042-018-6595-z78:7(8057-8073)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s11042-018-6595-z
Show More Cited By

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents