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Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
A Robust Watermarking Algorithm Based on Image Normalization and DC Coefficients
International Journal of Computer Science and Informatics
Abstract:
Digital watermarking is a highly evolving field, which involves the embedding of a certain kind of
information under a digital object (image, video, audio) for the purpose of copyright protection. Both
the image and the watermark are most frequently translated into a transform domain where the
embedding takes place. The selection of both the transform domain and the particular algorithm that is
used for the embedding of the watermark, depend heavily on the application. One of the most widely
used transform domains for watermarking of still digital images is the Discrete Cosine Transform
domain. The reason is that the Discrete Cosine Transform is a part of the JPEG standard, which in turn is
widely used for storage of digital images. In our research we propose a unique method for DCT-based
image watermarking. In an effort to achieve robustness to cropping and JPEG compression we have
developed an algorithm for rating the 8×8 blocks of the image DCT coefficients taking into account their
embedding capacity and their spatial location within the image. Our experiments show that the
proposed scheme offers adequate transparency, and works exceptionally well against cropping while at
the same time maintains sufficient robustness to JPEG compression.
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
(a) Block Diagram of the JPEG Compression
(b) Encoder
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
(c) Decoder
(d) Three Watermarks used in Project
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
Default Parameters
weighting factor alpha (recommended value ---):- 0.5
index of the coefficient - 60
embedding size (number of watermark coefficients per block) Choose 2, 4 o r 8:- 4
cropping:-0
quantization:-0
marked image in uint8:-0
normalization:-0
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
A: - stripes
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
SNR of real image, SNRr(dB)=12.5997
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
BER(bits per pixel)=0.0000
BERmod(bits per pixel with error)=NaN
rho=1.0000
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
B: - NPS logo
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
SNR of real image, SNRr(dB)=11.3263
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
BER (bits per pixel)=0.0000
BERmod (bits per pixel with error)=NaN
rho =1.0000
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
C: - random gray scale watermark
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
SNR of real image, SNRr(dB)=12.7750
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
BER (bits per pixel)=0.0000
BERmod (bits per pixel with error)=NaN
rho=1.0000
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
Future Enhancement:
Embedding the coefficients in a way that will take full advantage of the human visual system’s
characteristics is a big goal of the watermarking community. Further research in this subject is required
to investigate the possibility of incorporating our metric to the Just Noticeable Difference (JND) models
that have been proposed.
In addition, in this work the transparency of a watermarking algorithm is judged by the subjective
decision of independent observers. The possibility of developing a formal model for the evaluation of
the transparency may be investigated. However this task is not trivial. A simple correlation test between
the original and the marked image would not work. This would detect any differences between the two
but cannot tell if these differences occur in a visually perceptual manner. A JND model could be used as
the basis for the evaluation of the transparency ([24]), but then it should not also be used in the
embedding model. Otherwise the judgment would be biased and therefore unable to give dependable
results.
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
References:
[1] F. A. P. Petitcolas, R. J. Anderson, M. G. Kuhn, "Information Hiding – A Survey",
Proceedings of the IEEE, vol.87, no.7, pp.1062-1078, July 1999.
[2] D. J. Ryan, "Infosec and Infowar, Considerations for Military Intelligence",
www.danjryan.com/MIntl.html.
[3] F. Hartung, M. Kutter, "Multimedia Watermarking Techniques", Proceedings of the
IEEE, vol.87, no.7, pp.1079-1107, July 1999.
[4] I. J. Cox, M. L. Miller, J. A. Bloom, "Digital Watermarking", Morgan Kaufmann
Publishers, 2002.
[5] C. P. Pfleeger, "Security in Computing", Prentice Hall PTR, 2
nd
edition, 2000.
[6] G. L. Friedman, "The Trustworthy Digital Camera: Restoring Credibility to the
Photographic Image", IEEE Transactions on Consumer Electronics, vol.39, pp.905-910, October
1993.
[7] D. Kundur, D. Hatzinakos, “Digital Watermarking for Telltale Tamper Proofing and
Authentication”, Proceedings of the IEEE, vol.87, no.7, pp.1167-1180, July 1999.
[8] C. I. Podilchuk, E. J. Delp, "Digital Watermarking: Algorithm and Applications", IEEE
Signal Processing Magazine, pp.33-46, July 2001.
[9] C. C. Langelaar, I. Setyawan, R. L. Lagendijk, "Watermarking Digital Image and Video
Data", IEEE Signal Processing Magazine, pp.20-46, September 2000.
[10] W. Bender, D. Gruhl, N. Morimoto, "Techniques for Data Hiding", Proceedings SPIE,
vol.2420, p.40, San Jose, CA, February 1995.
[11] N. Nikolaidis, I. Pitas, "Copyright Protection of Images using Robust Digital
Signatures", Proceedings ICASSP '96, Atlanta, GA, May 1996.
[12] C. Langelaar, J. C. A. van der Lubbe, R. L. Lagendijk, "Robust Labeling Methods for
Copy Protection of Images", Proceedings in Electronic Imaging, vol.3022, pp.298-309, San Jose,
CA, February 1997.
[13] M. Kutter, F. Jordan, F. Bossen, "Digital Signature of Color Images using Amplitude
Modulation", Proceedings in Electronic Imaging, San Jose, CA, February 1997.
[14] M. Barni, C. I. Podilchuk, F. Bartolini, E. J. Delp, "Watermark Embedding: Hiding a
Signal within a Cover Image", IEEE Communications Magazine, pp.102-108, August 2001.
[15] M. Ramkumar, A. N. Akansu, A. A. Alatan, “On the Choice of Transforms for Data
Hiding in Compressed Video”, IEEE International Conference on Acoustics, Speech, and Signal
Processing 1999, Proceedings, Vol.6 , pp.3049-3052, 1999.
[16] S. Kang, Y. Aoki, “Digital Image Watermarking by Fresnel Transform and its
Robustness”, International Conference on Image Processing, Proceedings 1999 (ICIP 99), vol.2,
pp.221-225.
[17] J. J. K. O Ruanaidh, W. J. Dowling, F. M. Boland, "Phase Watermarking of Digital
Images", Proceedings IEEE, International Conference of Image Processing, vol.III, pp.239-242,
Lausanne, Switzerland, September 16-19, 1996.
[18] A. Herrigel, H. Petersen, J. O Ruanaidh, T. Pun, P. Shelby, "Copyright Techniques for
Digital Images Based on Asymmetric Cryptographic Techniques", presented at Workshop on
Information Hiding, Portland, Oregon, USA, April 1998.
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
[19] A. Herrigel, J. J. K. O Ruanaidh, H. Petersen, S. Pereira, T. Pun, "Secure Copyright
Protection Techniques for Digital Images", in Information Hiding (Lecture Notes in Computer
Science, vol. 1525), D. Aucsmith, Ed. Berlin, Germany: Springer, 1998, pp.169-190.
[20] S. Pereira, J. J. K. O Ruanaidh, F. Deguillaume, G. Csurka, T. Pun, "Template-based
Recovery of Fourier-based Watermarks using Log-polar and Log-log Maps", Proceedings IEEE in
Multimedia Systems 99, International Conference in Multimedia Computing and Systems, Florence,
Italy, June 7-11, 1999.
[21] J. J. K. O Ruanaidh, F. M. Boland, O. Sinnen, "Watermarking Digital Images for
Copyright Protection", Proceedings in Electronic Imaging and the Visual Arts 1996, Florence, Italy,
February 1996.
[22] I. J. Cox, J. Kilian, F. T. Leighton, T. Shamoon, “Secure Spread Spectrum
Watermarking for Multimedia”, IEEE Transactions on Image Processing, vol.6, no.12, pp.1673-
1687, December 1997.
[23] C. I. Podilchuk, W. Zeng, “Image-adaptive Watermarking using Visual Models”, IEEE
Journal on Selected Areas in Communications, vol.16, no.4, pp.525-539, May 1998.
[24] C. I. Podilchuk, W. Zeng, “Perceptual Watermarking of Still Images”, IEEE First
Workshop on Multimedia Signal Processing, pp.363-368, 1997.
[25] A. Piva, M. Barni, E. Bartolini, V. Cappellini, "A DCT-based Watermarking Recovering
without resorting to the Uncorrupted Digital Image", Proceedings IEEE, International Conference in
Image Processing, vol.1, p.520, Santa Barbara, CA, 1997.
[26] M. Barni, F. Bartolini, V. Cappellini, A. Lipi, A. Piva, "A DWT-based Technique for
Spatio-Frequency Masking of Digital Signatures", Proceedings SPIE/IS International Conferencein
Security and Watermarking of Multimedia Contents, vol.3657, pp.31-39, San Jose, January 25-27,
1999.
[27] K. Sayood, "Introduction to Data Compression", Morgan Kaufmann Publidhers, 2
nd
edition, 2000.
[28] J. Miano, "Compressed Image File Formats", Addison Wesley Longman, Inc, 1999.
Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf
[29] K. R Castleman, "Digital Image Processing", Prentice Hall, Inc, 1996.
[30] M. Ghanbari, "Video Coding: An Introduction to Standard Codecs", IEE
Telecommunication Series 42, 1999.
[31] C.-T. Hsu, J.-L. Wu, “Hidden Digital Watermarks in Images”, IEEE Transactions on
Image Processing, vol.8, no.1, pp. 58-68, January 1999.
[32] K. S. Shanmugan, A. M. Breipohl, "Random Signals: Detection Estimation and Data
Analysis", John Wiley and Sons, Inc, 1988.
[33] R. B Wolfgang, C. I. Podilchuk, E. J. Delp, “Perceptual Watermarks for Digital Images
and Video”, Proceedings of the IEEE, vol.87, no.7, pp. 1108-1126, July 1999.
[34] C. I. Podilchuk, E. J. Delp, "Digital Watermarking: Algorithm and Applications", IEEE
Signal Processing Magazine, pp.33-46, July 2001.
[35] Y.-P. Wang, M.-J. Chen, p.-Y. Cheng, “Robust Image Watermark With Wavelet
Transform and Spread Spectrum Techniques”, Conference Record of the Thirty-Fourth Asilomar
Conference on Signals, Systems and Computers, vol.2 , pp. 1846 –1850, Asilomar, 2000.
[36] S. B. Wicker, "Error Control Systems for Digital Communication and Storage",
Prentice-Hall Inc, 1995.
[37] I. Retsas, R. Pieper, R. Cristi, “Watermark Recovery with a DCT-based Scheme Employing
Nonuniform Imbedding”, 34
th
Southeastern Symposium on System Theory (SSST-02), Alabama,
March 18-19, 2002.

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A robust watermarking algorithm based on image normalization and dc coefficients

  • 1. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf A Robust Watermarking Algorithm Based on Image Normalization and DC Coefficients International Journal of Computer Science and Informatics Abstract: Digital watermarking is a highly evolving field, which involves the embedding of a certain kind of information under a digital object (image, video, audio) for the purpose of copyright protection. Both the image and the watermark are most frequently translated into a transform domain where the embedding takes place. The selection of both the transform domain and the particular algorithm that is used for the embedding of the watermark, depend heavily on the application. One of the most widely used transform domains for watermarking of still digital images is the Discrete Cosine Transform domain. The reason is that the Discrete Cosine Transform is a part of the JPEG standard, which in turn is widely used for storage of digital images. In our research we propose a unique method for DCT-based image watermarking. In an effort to achieve robustness to cropping and JPEG compression we have developed an algorithm for rating the 8×8 blocks of the image DCT coefficients taking into account their embedding capacity and their spatial location within the image. Our experiments show that the proposed scheme offers adequate transparency, and works exceptionally well against cropping while at the same time maintains sufficient robustness to JPEG compression.
  • 2. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf (a) Block Diagram of the JPEG Compression (b) Encoder
  • 3. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf (c) Decoder (d) Three Watermarks used in Project
  • 4. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf Default Parameters weighting factor alpha (recommended value ---):- 0.5 index of the coefficient - 60 embedding size (number of watermark coefficients per block) Choose 2, 4 o r 8:- 4 cropping:-0 quantization:-0 marked image in uint8:-0 normalization:-0
  • 5. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf A: - stripes
  • 6. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf SNR of real image, SNRr(dB)=12.5997
  • 7. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf BER(bits per pixel)=0.0000 BERmod(bits per pixel with error)=NaN rho=1.0000
  • 8. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf B: - NPS logo
  • 9. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf SNR of real image, SNRr(dB)=11.3263
  • 10. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf BER (bits per pixel)=0.0000 BERmod (bits per pixel with error)=NaN rho =1.0000
  • 11. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf C: - random gray scale watermark
  • 12. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf SNR of real image, SNRr(dB)=12.7750
  • 13. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf BER (bits per pixel)=0.0000 BERmod (bits per pixel with error)=NaN rho=1.0000
  • 14. Base paper: - http://ijcsi.org/papers/IJCSI-8-5-2-226-232.pdf Future Enhancement: Embedding the coefficients in a way that will take full advantage of the human visual system’s characteristics is a big goal of the watermarking community. Further research in this subject is required to investigate the possibility of incorporating our metric to the Just Noticeable Difference (JND) models that have been proposed. In addition, in this work the transparency of a watermarking algorithm is judged by the subjective decision of independent observers. The possibility of developing a formal model for the evaluation of the transparency may be investigated. However this task is not trivial. A simple correlation test between the original and the marked image would not work. This would detect any differences between the two but cannot tell if these differences occur in a visually perceptual manner. A JND model could be used as the basis for the evaluation of the transparency ([24]), but then it should not also be used in the embedding model. Otherwise the judgment would be biased and therefore unable to give dependable results.
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