The nature of statistical learning theory
The nature of statistical learning theory
A survey of RST invariant image watermarking algorithms
ACM Computing Surveys (CSUR)
Properties of orthogonal Gaussian-Hermite moments and their applications
EURASIP Journal on Applied Signal Processing
Adaptive watermark mechanism for rightful ownership protection
Journal of Systems and Software
RST Invariant Wavelet-Based Image Watermarking Using Template Matching Techniques
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05
A robust image watermarking algorithm using SVR detection
Expert Systems with Applications: An International Journal
IAS '09 Proceedings of the 2009 Fifth International Conference on Information Assurance and Security - Volume 01
Efficient general print-scanning resilient data hiding based on uniform log-polar mapping
IEEE Transactions on Information Forensics and Security
A new robust digital image watermarking based on Pseudo-Zernike moments
Multidimensional Systems and Signal Processing
Robust lossless image watermarking based on α-trimmed mean algorithm and support vector machine
Journal of Systems and Software
Image watermarking method in multiwavelet domain based on support vector machines
Journal of Systems and Software
Contourlet-based image watermarking using optimum detector in a noisy environment
IEEE Transactions on Image Processing
Geometric distortion insensitive image watermarking in affine covariant regions
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
The RST invariant digital image watermarking using Radon transforms and complex moments
Digital Signal Processing
A novel color image watermarking scheme in nonsampled contourlet-domain
Expert Systems with Applications: An International Journal
Research advances in data hiding for multimedia security
Multimedia Tools and Applications
The Shiftable Complex Directional Pyramid—Part I: Theoretical Aspects
IEEE Transactions on Signal Processing - Part I
Image watermarking based on invariant regions of scale-space representation
IEEE Transactions on Signal Processing
A New Digital Image Watermarking Algorithm Resilient to Desynchronization Attacks
IEEE Transactions on Information Forensics and Security
Still-image watermarking robust to local geometric distortions
IEEE Transactions on Image Processing
Reference Sharing Mechanism for Watermark Self-Embedding
IEEE Transactions on Image Processing
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Geometric distortion is known as one of the most difficult attacks to resist, for it can desynchronize the location of the watermark and hence causes incorrect watermark detection. It is a challenging work to design a robust image watermarking scheme against geometric distortions. Based on the least squares support vector machine (LS-SVM) geometric distortions correction, we propose a new image watermarking scheme in shiftable complex directional pyramid (PDTDFB) domain with good visual quality and reasonable resistance toward geometric distortions in this paper. Firstly, the PDTDFB decomposition is performed on the original host image. Then, the corresponding lowpass subband is divided into small blocks. Finally, the digital watermark is embedded into host image by modulating the selected lowpass PDTDFB coefficients in small blocks. The main steps of digital watermark detecting procedure include: (1) the PDTDFB decomposition is performed on the test images, and some low-order Gaussian-Hermite moment energy of highpass subbands are computed, which are regarded as the effective feature vectors; (2) the appropriate kernel function is selected for training, and a LS-SVM training model can be obtained; (3) the watermarked image is corrected with the well trained LS-SVM model; and (4) the digital watermark is extracted from the corrected watermarked image. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as filtering, noise adding, and JPEG compression etc, but also robust against the geometrical distortions.