On the computational aspects of Zernike moments
Image and Vision Computing
Circularly orthogonal moments for geometrically robust image watermarking
Pattern Recognition
A novel image watermarking scheme against desynchronization attacks by SVR revision
Journal of Visual Communication and Image Representation
Robust image watermarking using local Zernike moments
Journal of Visual Communication and Image Representation
A new robust digital image watermarking based on Pseudo-Zernike moments
Multidimensional Systems and Signal Processing
Local histogram based geometric invariant image watermarking
Signal Processing
Semi-fragile Zernike moment-based image water marking for authentication
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Geometric invariant semi-fragile image watermarking using real symmetric matrix
SIP'06 Proceedings of the 5th WSEAS international conference on Signal processing
Image reconstruction with polar zernike moments
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
On invariance analysis of Zernike moments in the presence of rotation with crop and loose modes
Multimedia Tools and Applications
Robust audio watermarking based on low-order zernike moments
IWDW'06 Proceedings of the 5th international conference on Digital Watermarking
Geometrically invariant image watermarking using Polar Harmonic Transforms
Information Sciences: an International Journal
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In image watermarking, the watermark robustness to geometric transformations is still an open problem. Using invariant image features to carry the watermark is an effective approach to addressing this problem. In this paper, a multibit geometrically robust image watermarking algorithm using Zernike moments is proposed. Some Zernike moments of an image are seleted, and their magnitudes are dither-modulated to embed an array of bits. The watermarked image is obtained via reconstruction from the modified moments and those left intact. In watermark extraction, the embedded bits are estimated from the invariant magnitudes of the Zernike moments using a minimum distance decoder. Simulation results show that the hidden message can be decoded at low error rates, robust against image rotation, scaling and flipping, and as well, a variety of other distortions such as lossy compression.