RST-invariant digital image watermarking based on log-polar mapping and phase correlation

Based on log-polar mapping (LPM) and phase correlation, the paper presents a novel digital image watermarking scheme that is invariant to rotation, scaling, and translation (RST). We embed a watermark in the LPMs of the Fourier magnitude spectrum of an original image, and use the phase correlation between the LPM of the original image and the LPM of the watermarked image to calculate the displacement of watermark positions in the LPM domain. The scheme preserves the image quality by avoiding computing the inverse log-polar mapping (ILPM), and produces smaller correlation coefficients for unwatermarked images by using phase correlation to avoid exhaustive search. The evaluations demonstrate that the scheme is invariant to rotation and translation, invariant to scaling when the scale is in a reasonable range, and very robust to JPEG compression.

[1]  BrownLisa Gottesfeld.  A survey of image registration techniques , 1992 .

[2]  Bernd Girod,et al.  Digital watermarking of raw and compressed video , 1996, Other Conferences.

[3]  Ahmed H. Tewfik,et al.  Progressive quantized projection watermarking scheme , 1999, MULTIMEDIA '99.

[4]  Ingemar J. Cox,et al.  Secure spread spectrum watermarking for multimedia , 1997, IEEE Trans. Image Process..

[5]  Frank Hartung,et al.  Multimedia watermarking techniques , 1999, Proc. IEEE.

[6]  Ingemar J. Cox,et al.  Rotation, scale, and translation resilient watermarking for images , 2001, IEEE Trans. Image Process..

[7]  Ronald N. Bracewell,et al.  The Fourier Transform and Its Applications , 1966 .

[8]  Jiying Zhao,et al.  A Video Copyright Protection System Based on ContentID , 2000 .

[9]  Wenjun Zeng,et al.  A statistical watermark detection technique without using original images for resolving rightful ownerships of digital images , 1999, IEEE Trans. Image Process..

[10]  Martin Kutter,et al.  Watermarking resistance to translation, rotation, and scaling , 1999, Other Conferences.

[11]  A.V. Oppenheim,et al.  The importance of phase in signals , 1980, Proceedings of the IEEE.

[12]  Edward J. Delp,et al.  Digital watermarking: algorithms and applications , 2001, IEEE Signal Process. Mag..

[13]  Thierry Pun,et al.  Robust template matching for affine resistant image watermarks , 2000, IEEE Trans. Image Process..

[14]  Lisa M. Brown,et al.  A survey of image registration techniques , 1992, CSUR.

[15]  David S. Young.  Straight Lines and Circles in the Log-Polar Image , 2000, BMVC.

[16]  Jeffrey A. Bloom,et al.  Computing the Probability of False Watermark Detection , 1999, Information Hiding.

[17]  Thierry Pun,et al.  Rotation, scale and translation invariant spread spectrum digital image watermarking , 1998, Signal Process..

[18]  Jiying Zhao,et al.  RST invariant digital image watermarking: importance of phase information , 2003, CCECE 2003 - Canadian Conference on Electrical and Computer Engineering. Toward a Caring and Humane Technology (Cat. No.03CH37436).

[19]  B. N. Chatterji,et al.  An FFT-based technique for translation, rotation, and scale-invariant image registration , 1996, IEEE Trans. Image Process..

[20]  Moshe Porat,et al.  Image characteristics and representation by phase: from symmetric to geometric structure , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[21]  Yehoshua Y. Zeevi,et al.  Image reconstruction from localized phase , 1992, IEEE Trans. Signal Process..

[22]  Ingemar J. Cox,et al.  Digital Watermarking , 2003, Lecture Notes in Computer Science.

[23]  Thierry Pun,et al.  Rotation, scale and translation invariant digital image watermarking , 1997, Proceedings of International Conference on Image Processing.

[24]  Jiying Zhao,et al.  LPM-based RST invariant digital image watermarking , 2003, CCECE 2003 - Canadian Conference on Electrical and Computer Engineering. Toward a Caring and Humane Technology (Cat. No.03CH37436).