Skip to main content
SpringerLink
Log in

Watermarking of digital images in frequency domain

  • Published:
International Journal of Automation and Computing Aims and scope Submit manuscript

Abstract

Invisible watermarking methods have been applied in frequency domains, trying to embed a small image inside a large original image. The original bitmap image will be converted into frequency domain to obtain the discrete cosine transform (DCT) matrices from its blocks. The bits of the logo image are embedded in random color components of the original image, as well as in random positions in each selected block. These positions are alternating current (AC) coefficients of the DCT matrix. The randomness is obtained from RC4 pseudorandom bit generator that determines in which color component this logo image bits will be embedded. The embedded bits have been hidden in random blocks in the image, which are chosen according to a (semi-random) function proposed in this work.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. B. C. Mohan, S. S. Kumar. A robust image watermarking scheme using singular value decomposition. Journal of Multimedia, vol. 3, no. 1, pp. 7–15, 2008.

    Article  Google Scholar 

  2. G. Lo-varco, W. Puech, M. Dumas. DCT-based watermarking method using color components. In Proceedings of the 2nd European Conference on Color in Graphics, Imaging and Vision, Aachen, Germany, pp. 146–150, 2004.

  3. A. Sverdlov, S. Dexter, A. M. Eskicioglu. Robust DCTSVD domain image watermarking for copyright protection: Embedding data in all frequencies. In Proceedings of International Multimedia Conference, Germany, pp. 166–174, 2004.

  4. E. H. Fu. Literature Survey on Digital Image Watermarking, Technical Report, EE381K-Multidimensional Signal Processing, 1998.

  5. G. Lo-varco, W. Puech, W. Dumas. Content based watermarking for securing color images. Journal of Imaging Science and Technology, vol. 49, no. 5, pp. 464–473, 2005.

    Google Scholar 

  6. S. P. Mohanty, P. Guturu, E. Kougianos, N. Pati. A novel invisible color image watermarking scheme using image adaptive watermark creation and robust insertionextraction. In Proceedings of the 8th IEEE International Symposium on Multimedia, IEEE, San Diego, USA, pp. 153–160, 2006.

    Google Scholar 

  7. L. Liu. A Survey on Digital Watermarking Technologies, Technical Report, Stony Brook University, New York, USA, 2005.

    Google Scholar 

  8. C. Coconu, V. Stoica, F. Ionescu, D. Profeta. Distributed implementation of discrete cosine transform algorithm on a network of workstations. In Proceedings of the International Workshop Trends & Recent Achievements in Information Technology, Romania, pp. 116–121, 2002.

  9. X. Y. Wang, J. Wu. A feature-based robust digital image watermarking against desynchronization attack. International Journal of Automation and Computing, vol. 4, no. 4, pp. 428–432, 2007.

    Article  Google Scholar 

  10. S. Bounkong, B. Toch, D. Saad, D. Lowe. ICA for watermarking digital images. Journal of Machine Learning Research, vol. 4, pp. 1471–1498, 2003.

    Article  Google Scholar 

  11. S. Pereira, T. Pun. A framework for optimal adaptive DCT watermarks. In Proceedings of the 10th European Signal Processing Conference, Finland, pp. 1669–1671, 2006.

  12. A. K. Parthasarathy. Improved Content Based Watermarking for images, M. Sc. dissertation, Louisiana State University, USA, 2006.

    Google Scholar 

  13. J. Seitz. Digital Watermarking for Digital Media, Information Science Publishing, 2005.

  14. JPEG, [Online], Available: http://jpeg.org/.

  15. W. Puech, J. M. Rodrigues. Crypto-compression of medical images by selective encryption of DCT. In Proceedings of the 13th European Signal Processing Conference, Antalya, Turkey, 2005.

  16. Y. Z. Lu. A novel face recognition algorithm for distinguishing faces with various angles. International Journal of Automation and Computing, vol. 5, no. 2, pp. 193–197, 2008.

    Article  Google Scholar 

  17. B. Schneier. Applied Cryptography, John Wiley and Sons, 1996.

Download references

Author information

Authors and Affiliations

  1. Faculty of Information Technology, Applied Science University, Amman, 11931, Jordan

    Sami E. I. Baba, Lala Z. Krikor, Thawar Arif & Zyad Shaaban

Authors
  1. Sami E. I. Baba
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lala Z. Krikor
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Thawar Arif
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zyad Shaaban
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sami E. I. Baba.

Additional information

This work was supported by the Deanship of Research and Graduate Studies at Applied Science University, Amman, Jordan.

Sami E. I. Baba graduated from Mansour University College, Iraq in 1992. He received the M. Sc. and Ph.D. degrees from University of Technology, Baghdad, Iraq in 1996 and 2000, respectively. He is currently an assistant professor at Computer Science Department, Faculty of Information Technology, Applied Science University, Amman, Jordan.

His research interests include grammatical inference, adaptive systems, image processing, and data hiding.

Lala Z. Krikor graduated from Mansour University College, Iraq in 1992. She received the M. Sc. and Ph.D. degrees from University of Technology, Baghdad, Iraq in 1996 and 2000, respectively. She is currently an assistant professor at Computer Science Department, Faculty of Information Technology, Applied Science University, Amman, Jordan.

Her research interests include image processing and information hiding.

Thawar Arif graduated from Control and Systems Engineering Department, University of Technology, Iraq. He received the M. Sc. degree in control and instrumentation engineering, and the Ph.D. degree in computer and control engineering, both from Baghdad University. He is currently the head of Computer Science Department at Applied Science University, Amman, Jordan. He is a member of the IEEE Computer Society and a professional member in the ACM.

His research interests include image retrieval, watermarking, adaptive control, and e-government.

Zyad Shaaban graduated from Computer Science Department, Yarmouk University, Irbid, Jordan in 1992. He received the Ph.D. degree in computer science from University of Technology, Johor Bahru, Malaysia in 1996. He is currently an assistant professor of computer science at the Faculty of Information Technology, Applied Science University, Jordan. He received a fellowship from University of Technology and he was working on handwritten text recognition project.

His research interests include handwritten character recognition, moments invariants, neural networks, face recognition, image retrieval, and arabic text recognition.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Baba, S.E.I., Krikor, L.Z., Arif, T. et al. Watermarking of digital images in frequency domain. Int. J. Autom. Comput. 7, 17–22 (2010). https://doi.org/10.1007/s11633-010-0017-7

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11633-010-0017-7

Keywords

Search

Navigation