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Multimedia Tools and Applications

, Volume 75, Issue 16, pp 9745–9755 | Cite as

Frequency domain digital watermark recognition using image code sequences with a back-propagation neural network

  • Chih-Ta YenEmail author
  • Yi-Jie Huang
Article

Abstract

Digital watermarking is an encryption technique commonly used to protect intellectual property and copyright. Although watermarks are a robust method of protecting property rights, environmental interference in image propagation through the Internet is inevitable, and human-based image modification can also destroy watermarks. In this study, watermarks (affected by noise interference) were embedded in a 256 × 256 pixel host image by using the discrete cosine transform (DCT) technique, which transfers the spatial domain of the host image into the frequency domain. Subsequently, 32 × 32 pixel watermarked images were embedded as watermark identification codes in the transferred frequency-domain-based host image. The inverse discrete cosine transform (IDCT) technique was used to alter the frequency of the spatial domain, thereby allowing the host image to be visible to the human eye. Several common interferences, such as salt-and-pepper noise, Gaussian noise, clipping, and rotation, were used to destroy the watermarked image. After the destruction process, the watermark was almost discernible in a slightly damaged state, but difficult to identify in a seriously damaged state after using the DCT watermarking scheme. In this study, a back-propagation neural network (BPNN) algorithm combined with a DCT watermarking scheme was used to suppress the interference affecting watermarks. The simulation results of using the proposed DCT-BPNN method indicated that the original watermarked image was restored considerably after being subjected to environmental interference during image propagation.

Keywords

Digital watermarking Discrete cosine transform (DCT) Salt-and-pepper noise Gaussian noise Clipping and rotation Back-propagation neural network (BPNN) 

Notes

Acknowledgments

This study was partially supported by the National Science Council under Grant No. 102-2622-E-150-016-CC3.

References

  1. 1.
    Ahmed KA, Ahmad HA, Gaydecki P (2009) A Blind Block Based DCT Watermarking Technique for Gray Level Images Using One Dimensional Walsh Coding. Current Trends in Information Technology (CTIT):1–6Google Scholar
  2. 2.
    Bhatnagar G, Raman B, Wu QMJ (2012) Robust watermarking using fractional wavelet packet transform. Image Processing, IET 6:386–397MathSciNetCrossRefGoogle Scholar
  3. 3.
    Chen Y, Chen J (2010) A Novel Blind Watermarking Scheme Based on Neural Networks for Image. Information Theory and Information Security (ICITIS):548–552Google Scholar
  4. 4.
    Cox IJ, Kilian J, Leighton FT, Shamoon T (1996) Secure spread spectrum watermarking for images, audio, and video. Proc Int Conf Image Proc 3:243–246CrossRefGoogle Scholar
  5. 5.
    Cox IJ, Kilian J, Leighton FT, Shamoon T (1997) Secure spread spectrum watermarking for multimedia. IEEE Trans Image Process 6:1673–1687CrossRefGoogle Scholar
  6. 6.
    Hu X, Lian X, Chen L, Zheng Y (2008) “Robust blind watermark algorithm of color image based on neural network”. Neural Net and Signal Proc 430–433Google Scholar
  7. 7.
    Kalker T, Epema DHJ, Hartel PH, Lagendijk RL, Van Steen M (2004) Music2Share - copyright-compliant music sharing in P2P systems. Proc IEEE 92:961–970CrossRefGoogle Scholar
  8. 8.
    Kaur R, Jindal S (2013) Semi-blind Image Watermarking Using High Frequency Band Based on DWT-SVD. 2013 6th International Conference on Emerging Trends in Engineering and Technology (ICETET), Nagpur:19 – 24Google Scholar
  9. 9.
    Mohananthini N, Yamuna G (2012) Watermarking for images using wavelet domain in Back-Propagation neural network,” Advances in Engineering, Science and Management:100 – 105Google Scholar
  10. 10.
    Nikolaidis N, Pitas I (1996) Copyright protection of images using robust digital signatures. Proc Int Conf Acoustics Speech and Signal Proc 4:2168–2171Google Scholar
  11. 11.
    Piva A, Barni M, Bartolini F, Cappellini V (1997) DCT-based watermark Rec overing without resorting to the Unc orrupted original image. Proc Int Conf Image Proc 1:520–523CrossRefGoogle Scholar
  12. 12.
    Raval MS, Joshi MV, Kher S (2013) Fuzzy Neural Based Copyright Protection Scheme for Superresolution. 2013 I.E. International Conference on Systems, Man, and Cybernetics (SMC), Manchester: 328 – 332Google Scholar
  13. 13.
    Seddik H, ESSTT Tunis Tunisia, Ben Braiek E (2013) Image securing based chaotic encryption coupled with DCT robust watermarking. 2013 International Conference on Electrical Engineering and Software Applications (ICEESA), Hammamet:1 – 6Google Scholar
  14. 14.
    Teng D, Shi R, Zhao X (2010) DCT Image Watermarking Technique Based on the Mix of Time-domain. Information Theory and Information Security (ICITIS):826–830Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Electrical EngineeringNational Formosa UniversityYunlinTaiwan

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