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Reseach Article

Accurate and Robust Identifying Forged Region Method in Scanned Images

by Zeinab F. Elsharkawy, Safey A. Abdelwahab, Sayed M. Elaraby, Moawad I. Dessouky, Fathi E. Abd El-samie
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 83 - Number 1
Year of Publication: 2013
Authors: Zeinab F. Elsharkawy, Safey A. Abdelwahab, Sayed M. Elaraby, Moawad I. Dessouky, Fathi E. Abd El-samie
10.5120/14415-2529

Zeinab F. Elsharkawy, Safey A. Abdelwahab, Sayed M. Elaraby, Moawad I. Dessouky, Fathi E. Abd El-samie . Accurate and Robust Identifying Forged Region Method in Scanned Images. International Journal of Computer Applications. 83, 1 ( December 2013), 40-47. DOI=10.5120/14415-2529

@article{ 10.5120/14415-2529,
author = { Zeinab F. Elsharkawy, Safey A. Abdelwahab, Sayed M. Elaraby, Moawad I. Dessouky, Fathi E. Abd El-samie },
title = { Accurate and Robust Identifying Forged Region Method in Scanned Images },
journal = { International Journal of Computer Applications },
issue_date = { December 2013 },
volume = { 83 },
number = { 1 },
month = { December },
year = { 2013 },
issn = { 0975-8887 },
pages = { 40-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume83/number1/14415-2529/ },
doi = { 10.5120/14415-2529 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:58:17.390132+05:30
%A Zeinab F. Elsharkawy
%A Safey A. Abdelwahab
%A Sayed M. Elaraby
%A Moawad I. Dessouky
%A Fathi E. Abd El-samie
%T Accurate and Robust Identifying Forged Region Method in Scanned Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 83
%N 1
%P 40-47
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Digital images have been spread all over the world. With rapidly development and ease of use of digital image editing tools like Photoshop TM and paint TM, it is important to authenticate or detect the forged regions in any suspicious digital image. In this paper, new and robust method for authenticating and identifying the forged regions in the scanned images is proposed. The method is based on using dust/scratch and source imperfection pattern of scanned images to identify the forged regions. Each suspicious image is divided into non-overlapping blocks. The correlation features between each block and acquisition scanner's template have been extracted to identify the correct scanned blocks and the tampered ones. Four groups of the tampered images are tested. The experimental results have approved the validity, efficiency, and robustness of the proposed method to identify the tampered images and define their forged regions. The proposed results are then compared to the results of the two previously published methods. The proposed method is simple and easy to apply to all types of the tampered images, regardless the acquisition source noise or the image contents.

References
  1. H. Sencar, N. Memon, "Overview of state-of-the art in digital image forensics," WSPC - Proceedings Trim Size: 9. 75in x 6. 5in sencar-memon-chapter. 1, September 25, 2007.
  2. N. Khanna, A. Mikkilineni, A. Martone,G. Ali, G. Chiu, J. Allebach, E. Delp, "A survey of forensic characterization methods for physical devices," Digit Investig, vol. 3, pp. 17–28, September2006.
  3. T. Gloe, E. Franz, and A. Winkler, "Forensics for flatbed scanners," in Proc. SPIE Security, Steganography, and Watermarking of Multimedia Contents IX, San Jose, CA, USA, vol. 6505, p. 65051I, Feb. 2007.
  4. A. Kot, H. Cao,"Image and Video Source Class Identification," in proc. Digital Image Forensics, Springer, pp 157-178, 2013.
  5. T. Gloe, E. Franz, and A. Winkler, "Forensics for flatbed scanners," in Proc. SPIE Security, Steganography, and Watermarking of Multimedia Contents IX, San Jose, CA, USA, vol. 6505, pp. 65051I, Feb. 2007.
  6. H. Gou, A. Swaminathan, and M. Wu, "Robust scanner identification based on noise features," in Proc. SPIE Security, Steganography, and Watermarking of Multimedia Contents IX, San Jose, CA, USA, vol. 6505, pp. 65050S, Jan. 2007.
  7. N. Khanna and E. Delp, "Source Scanner Identification for Scanned Documents," IEEE International Workshop on Information Forensics and Security - WIFS , 2009
  8. P. Chiang, N. Khanna, A. Mikkilineni, M. Segovia, J. Allebach, G. Chiu, E. Delp ,"Printer and Scanner Forensics: Models and Methods," Intelligent Multimedia Analysis for Security Applications, Studies in Computational Intelligence Volume 282, pp 145-187, 2010.
  9. N. Khanna, A. Mikkilineni, G. Chiu, J. Allebach, and E. Delp, "Scanner identification using sensor pattern noise," in Proc. SPIE Security, Steganography, and Watermarking of Multimedia Contents IX, San Jose, CA, USA, vol. 6505, p. 65051K, Feb. 2007.
  10. N. Khanna, A. Mikkilineni, and E. Delp,"Scanner Identification Using Feature-Based Processing and Analysis," Information Forensics and Security, IEEE Transactions on, Vol. 4, No. 1, pp. 123-139, MARCH 2009.
  11. N. Khanna, T. George, J. Allebach; Delp, J. Edward ,"Scanner Identification with Extension to Forgery Detection," Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, Volume 6819, pp. 68190G-68190G-10, 2008.
  12. N. Khanna, G. Chiu, J. Allebach, E. Delp," Forensic techniques for classifying scanner, computer generated and digital camera images," In: Proceedings of the IEEE international conference on acoustics, speech and signal processing, pp 1653–1656. Las Vegas, NV, 2008.
  13. C. Choi, M. Lee, H. Lee, "Scanner identification using spectral noise in the frequency domain," in Proc. IEEE International Conference on Image Processing (ICIP), Hong Kong, pp. 2121 – 2124, 26-29 Sept. 2010.
  14. C. Choi, M. Lee, D. Hyun, H. Lee, "Forged Region Detection for Scanned Images," Computer Science and Convergence Lecture Notes in Electrical Engineering Volume 114, pp 687-694, 2012.
  15. Z. Elsharkawy, S. Abdelwahab, M. Dessouky, S. Elaraby, F. Abd El-Samie, "Identifying Unique Flatbed Scanner Characteristics for Matching a Scanned Image to its source," in Proc. CiiT International Journal of Digital Image Processing, Vol 5, No 9, September 2013.
  16. J. Yoo, T. Han," Fast Normalized Cross-Correlation", in Proc. Circuits, Systems and Signal Processing, Springer, vol. 28, Issue. 6, pp. 819-843, December 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Digital Forensics Scanner Identification Forgery Detection Image Processing.