A Normalization-based Robust Image Watermarking Scheme Using SVD and DCT
Digital watermarking is one of the techniques for
copyright protection. In this paper, a normalization-based robust
image watermarking scheme which encompasses singular value
decomposition (SVD) and discrete cosine transform (DCT)
techniques is proposed. For the proposed scheme, the host image is
first normalized to a standard form and divided into non-overlapping
image blocks. SVD is applied to each block. By concatenating the
first singular values (SV) of adjacent blocks of the normalized image,
a SV block is obtained. DCT is then carried out on the SV blocks to
produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency
band of a SVD-DCT block by imposing a particular
relationship between two pseudo-randomly selected DCT
coefficients. An adaptive frequency mask is used to adjust local
watermark embedding strength. Watermark extraction involves
mainly the inverse process. The watermark extracting method is blind
and efficient. Experimental results show that the quality degradation
of watermarked image caused by the embedded watermark is visually
transparent. Results also show that the proposed scheme is robust
against various image processing operations and geometric attacks.
[1] S.W. Foo, H.S. Muh, and N.M. Mei "Image watermarking using timefrequency
compression expansion" IEEE International Symposium on
Circuits and Systems, 2004, pp. 201-204.
[2] S.W. Foo, X. Feng, and M. Li "A blind imagewatermarking scheme
using peak point extraction", IEEE International Symposium on Circuits
and Systems, 2005, pp. 4409-4412.
[3] M. Acevedo, "Image watermarking: properties, techniques and
evaluation. Multimedia security: Steganography and Digital
Watermarking Techniques for Protection of Intellectual Property, Idea
Group Publishing. Pennsylvania, 2005.
[4] S.W. Foo, Y.T. Hee, and H.D. Yan, "An adaptive image watermarking
system", IEEE Tencon 2005, pp. 509-513.
[5] N. Cvejic and T. Seppänen, "Audio watermarking: requirement,
algorithms, and benchmarking". Digital watermarking for digital media,
Information Science Publishing, Pennsylvania, 2005.
[6] J. Foote, J. Adco, and A. Girgensohn, "Time base modulation: a new
approach to watermarking audio" [Electronic Version], Palo Alto
Laboratory. California. 2003.
[7] M.A. Suhail, "Digital watermarking for protection of intellectual
property". Multimedia security: steganography and digital
watermarking techniques for protection of intellectual property, Idea
Group Publishing. Pennsylvania, 2006.
[8] P. Bassia, W.T. Pitas, "Robust Audio Watermarking In Time Domain",
EUSIPCO 1998, 8-11 Sept., Patras, Greece, pp. 25-28.
[9] D. Gruhl, A. Lu, and W. Bender, "Echo Hiding for Watermarking", in
Proc. Information Hiding Workshop, University of Cambridge, U.K.,
1999, pp. 295-315.
[10] K. Seits, and T. Jahnke, "Digital watermarking: an introduction". In
Seits, J, Digital watermarking for digital media, Information Science
Publishing. Pennsylvania, 2006.
[11] R. Garcia, "Digital Watermarking of Audio Signals Using a
Psychoacoustic Auditory Model and Spread Spectrum Theory", 107th
Convention, Audio Engineering Society, New York, 1999.
[12] H.J. Kim, Y.H. Choi & J.W. Seok and K.H. Hong. "Audio
Watermarking Techniques: Intelligent Watermarking Techniques".
Chapter 8, 185-218, 2005.
[13] J, Seitz, S.H. Michale, "Digital Watermarking for Digital Media,"
Information Science Publishing, 2005.
[14] N. Cvejic and T. Seppänen, "Increasing robustness of LSB audio
steganography by reduced distortion LSB coding," Journal of
University Computer Science, vol 11, p56, 2006.
[15] C. Hsieh. & P. Tsou. "Blind Cepstrum Domain Audio Watermarking
Based on Time Energy Features". 4th Int. Conf. on Digital Signal
Processing, 705-708, 2004.
[16] K.N. Garcia. "Digital Watermarking of Audio Signals Using a
Psychoacoustic Auditory Model and Spread Spectrum Theory". 107th
Convention, Audio Engineering Society, preprint 5073, 2006.
[17] L. Wu, P.C. Su and M. Kuo "Robust Audio Watermarking for Copyright
Protection". SPIE-s 44th Annual Meeting Advanced Signal Processing
Algorithms, Architectures, and Implementations IX. 2003.
[18] B. Vladimir, K.E. Rao. "An Efficient Implementation of the Forward
and Inverse MDCT in MPEG Audio Coding". IEEE Signal Processing
Letters, Vol.8, No.2, 2005.
[1] S.W. Foo, H.S. Muh, and N.M. Mei "Image watermarking using timefrequency
compression expansion" IEEE International Symposium on
Circuits and Systems, 2004, pp. 201-204.
[2] S.W. Foo, X. Feng, and M. Li "A blind imagewatermarking scheme
using peak point extraction", IEEE International Symposium on Circuits
and Systems, 2005, pp. 4409-4412.
[3] M. Acevedo, "Image watermarking: properties, techniques and
evaluation. Multimedia security: Steganography and Digital
Watermarking Techniques for Protection of Intellectual Property, Idea
Group Publishing. Pennsylvania, 2005.
[4] S.W. Foo, Y.T. Hee, and H.D. Yan, "An adaptive image watermarking
system", IEEE Tencon 2005, pp. 509-513.
[5] N. Cvejic and T. Seppänen, "Audio watermarking: requirement,
algorithms, and benchmarking". Digital watermarking for digital media,
Information Science Publishing, Pennsylvania, 2005.
[6] J. Foote, J. Adco, and A. Girgensohn, "Time base modulation: a new
approach to watermarking audio" [Electronic Version], Palo Alto
Laboratory. California. 2003.
[7] M.A. Suhail, "Digital watermarking for protection of intellectual
property". Multimedia security: steganography and digital
watermarking techniques for protection of intellectual property, Idea
Group Publishing. Pennsylvania, 2006.
[8] P. Bassia, W.T. Pitas, "Robust Audio Watermarking In Time Domain",
EUSIPCO 1998, 8-11 Sept., Patras, Greece, pp. 25-28.
[9] D. Gruhl, A. Lu, and W. Bender, "Echo Hiding for Watermarking", in
Proc. Information Hiding Workshop, University of Cambridge, U.K.,
1999, pp. 295-315.
[10] K. Seits, and T. Jahnke, "Digital watermarking: an introduction". In
Seits, J, Digital watermarking for digital media, Information Science
Publishing. Pennsylvania, 2006.
[11] R. Garcia, "Digital Watermarking of Audio Signals Using a
Psychoacoustic Auditory Model and Spread Spectrum Theory", 107th
Convention, Audio Engineering Society, New York, 1999.
[12] H.J. Kim, Y.H. Choi & J.W. Seok and K.H. Hong. "Audio
Watermarking Techniques: Intelligent Watermarking Techniques".
Chapter 8, 185-218, 2005.
[13] J, Seitz, S.H. Michale, "Digital Watermarking for Digital Media,"
Information Science Publishing, 2005.
[14] N. Cvejic and T. Seppänen, "Increasing robustness of LSB audio
steganography by reduced distortion LSB coding," Journal of
University Computer Science, vol 11, p56, 2006.
[15] C. Hsieh. & P. Tsou. "Blind Cepstrum Domain Audio Watermarking
Based on Time Energy Features". 4th Int. Conf. on Digital Signal
Processing, 705-708, 2004.
[16] K.N. Garcia. "Digital Watermarking of Audio Signals Using a
Psychoacoustic Auditory Model and Spread Spectrum Theory". 107th
Convention, Audio Engineering Society, preprint 5073, 2006.
[17] L. Wu, P.C. Su and M. Kuo "Robust Audio Watermarking for Copyright
Protection". SPIE-s 44th Annual Meeting Advanced Signal Processing
Algorithms, Architectures, and Implementations IX. 2003.
[18] B. Vladimir, K.E. Rao. "An Efficient Implementation of the Forward
and Inverse MDCT in MPEG Audio Coding". IEEE Signal Processing
Letters, Vol.8, No.2, 2005.
@article{"International Journal of Electrical, Electronic and Communication Sciences:60782", author = "Say Wei Foo and Qi Dong", title = "A Normalization-based Robust Image Watermarking Scheme Using SVD and DCT", abstract = "Digital watermarking is one of the techniques for
copyright protection. In this paper, a normalization-based robust
image watermarking scheme which encompasses singular value
decomposition (SVD) and discrete cosine transform (DCT)
techniques is proposed. For the proposed scheme, the host image is
first normalized to a standard form and divided into non-overlapping
image blocks. SVD is applied to each block. By concatenating the
first singular values (SV) of adjacent blocks of the normalized image,
a SV block is obtained. DCT is then carried out on the SV blocks to
produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency
band of a SVD-DCT block by imposing a particular
relationship between two pseudo-randomly selected DCT
coefficients. An adaptive frequency mask is used to adjust local
watermark embedding strength. Watermark extraction involves
mainly the inverse process. The watermark extracting method is blind
and efficient. Experimental results show that the quality degradation
of watermarked image caused by the embedded watermark is visually
transparent. Results also show that the proposed scheme is robust
against various image processing operations and geometric attacks.", keywords = "Image watermarking, Image normalization, Singularvalue decomposition, Discrete cosine transform, Robustness.", volume = "4", number = "1", pages = "182-6", }