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Information Hiding and Applications pp 75–114Cite as

Robust Image Watermarking Based on Scale-Space Feature Points

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 227))

Summary

Digital watermarking techniques have been explored extensively since its first appearance in the 1990s. However, watermark robustness to geometric attacks is still an open problem. The past decade has witnessed a significant improvement in the understanding of geometric attacks and how watermarks can survive such attacks. In this chapter, we will introduce a set of image watermarking schemes which can resist both geometric attacks and traditional signal processing attacks simultaneously. These schemes follow a uniform framework, which is based on the detection of scale-space feature points. We call it the scale-space feature point based watermarking, SSFW for short. Scale-space feature points have been developed recently for pattern recognition applications. This kind of feature points are commonly invariant to rotation, scaling and translation (RST), therefore they naturally fit into the framework of geometrically robust image watermarking. Scale-space feature points are typically detected from the scale space of the image. As a result, we will first introduce the scale space theory and how the feature points can be extracted. The basic principles on how the scale-space feature points can be adapted for watermark synchronization are then discussed in detail. Subsequently, we will present several content-based watermark embedding and extraction methods which can be directly implemented based on the synchronization scheme. A detailed watermarking scheme which combines scale-invariant feature transform (SIFT) and Zernike moments is then presented for further understanding of SSFW. Watermarking schemes based on the SSFW framework have the following advantages: (a) Good invisibility. The Peak Signal to Noise Ratio (PSNR) value is typically higher than 40dB. (b) Good robustness. These schemes can resist both signal processing attacks and geometric attacks, such as JPEG compression, image filtering, added noise, RST attacks, locally cropping as well as some combined attacks.

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References

  1. Alghoniemy, M., Tewfik, A.: Geometric invariance in image watermarking. IEEE Trans. Image Processing 13, 145–153 (2004)

    Article  Google Scholar 

  2. Bas, P., Chassery, J., Macq, B.: Geometrically invariant watermarking using feature points. IEEE Trans. Image Processing 11, 1014–1028 (2002)

    Article  Google Scholar 

  3. Cox, I.J., Miller, M.L., Bloom, J.A.: Digital Watermarking: Principles & Practice. Morgan Kaufman, Los Altos (2001)

    Google Scholar 

  4. Delannay, D., Macq, B.: Generalized 2D cyclic patterns for secret watermark generation. In: Proc. Int’l Conf. Image Processing, vol. 2, pp. 72–79 (2000)

    Google Scholar 

  5. Kim, H., Lee, H.: Invariant image watermark using Zernike moments. IEEE Trans. Circuits and Systems for Video Technology 13, 766–775 (2003)

    Article  Google Scholar 

  6. Kutter, M.: Watermarking resisting to translation, rotation, and scaling. In: Proc. SPIE Multimedia Systems and Applications, vol. 3528, pp. 423–431 (1999)

    Google Scholar 

  7. Kutter, M., Bhattacharjee, S., Ebrahimi, T.: Towards second generation watermarking schemes. In: Proc. Int’l Conf. Image Processing, vol. 1, pp. 320–323 (1999)

    Google Scholar 

  8. Lee, H., Kim, H., Lee, H.: Robust image watermarking using local invariant features. Optical Engineering 45, 037002 (2006)

    Article  Google Scholar 

  9. Lee, H., Lee, H.: Copyright protection through feature-based watermarking using scale-invariant keypoints. In: Proc. Int’l Conf. Consumer Electronics, pp. 225–226 (2006)

    Google Scholar 

  10. Li, L., Guo, B., Shao, K.: Geometrically robust image watermarking using scale-invariant feature transform and Zernike moments. Chinese Optics Letters 5, 332–335 (2007)

    Google Scholar 

  11. Licks, V., Jordan, R.: Geometric attacks on image watermarking systems. IEEE Multimedia 12, 68–78 (2005)

    Article  Google Scholar 

  12. Lin, C., Wu, M., Bloom, J., Cox, I., Miller, M., Lui, Y.: Rotation, scale, and translation resilient watermarking of images. IEEE Trans. Image Processing 10, 767–782 (2001)

    Article  MATH  Google Scholar 

  13. Lindeberg, T.: Scale-space theory: a basic tool for analysing structures at different scales. Journal of Applied Statistics 21, 224–270 (1994)

    Article  Google Scholar 

  14. Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 91–110 (2004)

    Article  Google Scholar 

  15. Lu, W., Lu, H., Chung, F.: Feature based watermarking using watermark template match. Applied Mathematics and Computation 177, 377–386 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  16. Mikolajczyk, K., Schmid, C.: Indexing based on scale invariant interest points. In: Proc. Int’l Conf. Computer Vision, vol. 1, pp. 525–531 (2001)

    Google Scholar 

  17. O’Ruanaidh, J., Pun, T.: Rotation, scale and translation invariant spread spectrum digital image watermarking. Signal Processing 63, 303–317 (1998)

    Article  Google Scholar 

  18. Pan, J.S., Huang, H.C., Jain, L.C. (eds.): Intelligent Watermarking Techniques. World Scientific Publishing Company, Singapore (2004)

    MATH  Google Scholar 

  19. Pan, J.S., Huang, H.C., Jain, L.C., Fang, W.C. (eds.): Intelligent Multimedia Data Hiding. Springer, Heidelberg (2007)

    Google Scholar 

  20. Pereira, S., Pun, T.: Robust template matching for affine resistant image watermarks. IEEE Trans. Image Processing 9, 1123–1129 (2000)

    Article  Google Scholar 

  21. Qi, X., Qi, J.: A robust content-based digital image watermarking scheme. Signal Processing 87, 1264–1280 (2007)

    Article  Google Scholar 

  22. Seo, J., Yoo, C.: Localized image watermarking based on feature points of scale-space representation. Pattern Recognition 37, 1365–1375 (2004)

    Article  MATH  Google Scholar 

  23. Tang, C., Hang, H.: A feature-based robust digital image watermarking scheme. IEEE Trans. Signal Processing 51, 950–959 (2003)

    Article  MathSciNet  Google Scholar 

  24. Xin, Y., Liao, S., Pawlak, M.: Geometrically robust image watermarking via pseudo-Zernike moments. In: Proc. Canadian Conf. Electrical and Computer Engineering, vol. 2, pp. 939–942 (2004)

    Google Scholar 

  25. Xin, Y., Liao, S., Pawlak, M.: Robust data hiding with image invariants. In: Proc. Canadian Conf. Electrical and Computer Engineering, pp. 963–966 (2005)

    Google Scholar 

  26. Xin, Y., Liao, S., Pawlak, M.: Circularly orthogonal moments for geometrically robust image watermarking. Pattern Recognition 40, 3740–3752 (2007)

    Article  MATH  Google Scholar 

  27. Yu, G., Lu, C., Liao, H.: Mean-quantization-based fragile watermarking for image authentication. Optical Engineering 40, 1396–1408 (2001)

    Article  Google Scholar 

  28. Zheng, D., Liu, Y., Zhao, J., El-Saddik, A.: A survey of RST invariant image watermarking algorithms. ACM Computing Surveys 39, 1–89 (2007)

    Article  Google Scholar 

  29. Zheng, D., Zhao, J., ElSaddik, A.: RST-invariant digital image watermarking based on log-polar mapping and phase correlation. IEEE Trans. Circuits and Systems for Video Technology 13, 753–765 (2003)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Intelligent Control and Image Engineering (ICIE), Xidian University, Xi’an, 710071, P.R. China

    Bao-Long Guo & Lei-Da Li

  2. National Kaohsiung University of Applied Sciences, Kaohsiung, 807, Taiwan

    Jeng-Shyang Pan

Authors
  1. Bao-Long Guo
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  2. Lei-Da Li
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  3. Jeng-Shyang Pan
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Editor information

Editors and Affiliations

  1. National Kaohsiung University of Applied Sciences, No.415, Jiangong Rd., Sanmin District, 80778, Kaohsiung City, Taiwan (R.O.C.)

    Jeng-Shyang Pan

  2. Department of Electrical Engineering, National University of Kaohsiung, No.700, Kaohsiung University Rd., Nan Tzu Dist., 811, Kaohsiung, Taiwan (R.O.C.)

    Hsiang-Cheh Huang

  3. University of South Australia, Mawson Lakes Campus, Sa 5095, Adelaide, South Australia, Australia

    Lakhmi C. Jain

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© 2009 Springer-Verlag Berlin Heidelberg

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Guo, BL., Li, LD., Pan, JS. (2009). Robust Image Watermarking Based on Scale-Space Feature Points. In: Pan, JS., Huang, HC., Jain, L.C. (eds) Information Hiding and Applications. Studies in Computational Intelligence, vol 227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02335-4_5

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  • DOI: https://doi.org/10.1007/978-3-642-02335-4_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02334-7

  • Online ISBN: 978-3-642-02335-4

  • eBook Packages: EngineeringEngineering (R0)

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