Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
The nature of statistical learning theory
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Human visual system based adaptive digital image watermarking
Signal Processing
A robust image watermarking algorithm using SVR detection
Expert Systems with Applications: An International Journal
IEEE Transactions on Image Processing
Invariant image watermarking using multi-scale Harris detector and wavelet moments
Computers and Electrical Engineering
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IEEE Transactions on Information Forensics and Security
Image watermarking method in multiwavelet domain based on support vector machines
Journal of Systems and Software
Geometric distortion insensitive image watermarking in affine covariant regions
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A Robust Watermarking Algorithm against Geometric Distortions
ISIP '10 Proceedings of the 2010 Third International Symposium on Information Processing
Image watermarking based on invariant regions of scale-space representation
IEEE Transactions on Signal Processing
Geometrically invariant image watermarking using Polar Harmonic Transforms
Information Sciences: an International Journal
A New Digital Image Watermarking Algorithm Resilient to Desynchronization Attacks
IEEE Transactions on Information Forensics and Security
Performance evaluation of moment-based watermarking methods: A review
Journal of Systems and Software
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IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Neural Networks
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In this paper, a robust digital image watermarking algorithm is proposed based on fuzzy support vector machine (FSVM) correction. The significant bitplane image is extracted from original host, and undecimated discrete wavelet transform (UDWT) is performed on the significant bitplane image. The lowpass subband is divided into small blocks, and digital watermark is embedded into original host by adaptively modulating the selected wavelet coefficients in small blocks. In order to resist geometric distortion attacks, FSVM is utilized to learn geometric distortion parameters by using low order Zernike moments. The watermark extraction is carried out after watermarked image has been synchronized without original host. Simulation also shows outstanding robustness of the proposed algorithm against most common image processing operations and geometric distortions.