Skip to main content
SpringerLink
Log in

An Anti-cropping Watermarking Method for Facial Images Using Prediction and Weber Ratio Techniques

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

When a digital facial image is published in any social network, often the facial part of the image is cropped and abused without the owner permission. It is extremely difficult to verify the owner, especially in cases where the embedded watermark does not cover the cropped face part. This paper proposes a digital image watermarking method that is robust against cropping attack in the spatial domain for protecting the copyright of facial images. The face region in an image is evaluated by using phase correlation technique for embedding the watermark. A binary watermark is defined to be embedded in the facial region. Pixels for embedding the watermark are predicted and altered based on the Weber ratio to control the strength of the watermark in order to make it imperceptible to the human eye. The watermark is extracted from the watermarked image that does not require the original image by subtracting the watermarked pixel from its predicted pixel. After this, the pieces of the extracted watermarks are verified to measure their similarity with the original watermark. The experimental results show that our method yielded 82 % similarity with the original watermark image, when it was attacked by the cropping attacks for any shapes, sizes, locations and the JPEG compression.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24

Similar content being viewed by others

References

  1. Cox, I. J., Kilian, I., Leighton, F. T., & Shamoon, T. (1997). Secure spread spectrum watermarking for multimedia. IEEE Transactions on Image Processing, 6(12), 1673–1687.

    Article  Google Scholar 

  2. Xia, X. G, Boncelet, C. G., & Arce, G. R. (1997). A multiresolution watermark for digital images. In IEEE international conference on image processing (Vol. 1, pp. 548–551).

  3. Inoue, H., Miyazaki, A., & Katsura, T. (1999). An image watermarking method based on the wavelet transform. In IEEE international conference on image processing (Vol. 1, pp. 296–300).

  4. Ni, R., &Ruan, Q. (2006, September). Region of interest watermarking based on fractal dimension. In The 18th international conference on pattern recognition (Vol. 3, pp. 934–937).

  5. Phiasai, T., Kumhom, P., & Chamnongthai, K. (2004, October 26–29). A digital image watermarking technique using prediction method and weber ratio. In IEEE international symposium on communications and information technologies (Vol. 1, pp. 314–317).

  6. Phadikar, A., Maity, S. P., & Rahaman, H. (2009, March 6–7). Region specific spatial domain image watermarking scheme. In IEEE international advance computing conference (pp. 888–893).

  7. Nikolaidis, A., & Pitas, I. (2001). Region-based image watermarking. IEEE Transactions on Image Processing, 10(11), 1726–1740.

    Article  MATH  Google Scholar 

  8. Phiasai, T., Kumhom, P., & Chamnongthai, K. (2003, July). A method for reconstructing watermark from cropped watermarked image. In ITC CSCC (Vol. 1, pp. 108–111).

  9. Abdullatif, M., Zeki, A. M., Chebil, J., & Gunawan, T. S. (2013, March 8–10). Properties of digital image watermarking. In IEEE 9th international colloquium on signal processing and its applications (pp. 235–240).

  10. Nin, J., & Ricciardi, S. (2013). Digital watermarking techniques and security issues in the information in the information and communication society. In International conference on advanced information networking and applications workshops (pp. 1553–1558).

  11. Zhang, Y. (2003). Digital watermarking technology: A review. In International conference on future computer and communication (pp. 250–252).

  12. Lee, J. S., & Li, B. (2014). Self-recognized image protection technique that resists large-scale cropping. IEEE Multimedia, 21, 60–73.

    Article  Google Scholar 

  13. Phiasai, T., Arunrungrusmi, S., & Chamnongthai, K. (2001). Face recognition system with PCA and moment invariant method. In The 2001 IEEE international symposium on circuits and systems (ISCAS) (Vol. 2, pp. 165–168).

  14. Li, W., & Xiang, H. Y. (2009). Face detection based on QFT phase-only correlation template match. In International conference on information science and engineering (pp. 1231–1234).

  15. Voloshynovskiy, S., Deguillaume, F., & Pun, T. (2001). Multibit digital watermarking robust against local nonlinear geometrical distortions. In International conference on image processing (Vol. 3, pp. 999–1002).

  16. Foroosh, H., Zerubia, J. B., & Berthod, M. (2002). Extension of phase correlation to subpixel registration. IEEE Transactions on Image Processing, 11, 188–200.

    Article  Google Scholar 

  17. Gonzalez, R. C., & Woods, R. E. (2002). Digital image processing (2nd ed.). Upper Saddle River: Prentice-Hall.

    Google Scholar 

Download references

Acknowledgments

I would like to express my sincere thanks and gratitude to Asst. Prof. Dr. Pinit Kumhom whose valuable knowledge and suggestion helped me in writing the contents of this paper.

Author information

Authors and Affiliations

  1. Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Tejtasin Phiasai & Kosin Chamnongthai

  2. School of Information Technology, Mae Fah Luang University, Chiang Rai, Thailand

    Punnarumol Temdee

Authors
  1. Tejtasin Phiasai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Punnarumol Temdee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kosin Chamnongthai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tejtasin Phiasai.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Phiasai, T., Temdee, P. & Chamnongthai, K. An Anti-cropping Watermarking Method for Facial Images Using Prediction and Weber Ratio Techniques. Wireless Pers Commun 85, 421–448 (2015). https://doi.org/10.1007/s11277-015-2747-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-015-2747-x

Keywords

Search

Navigation