A DCT-domain system for robust image watermarking
Signal Processing
Robust image watermarking in the spatial domain
Signal Processing
Attack modelling: towards a second generation watermarking benchmark
Signal Processing - Special section on information theoretic aspects of digital watermarking
Improved Robust Watermarking in DCT Domain for Color Images
AINA '04 Proceedings of the 18th International Conference on Advanced Information Networking and Applications - Volume 2
A new wavelet based logo-watermarking scheme
Pattern Recognition Letters
An image adaptive, wavelet-based watermarking of digital images
Journal of Computational and Applied Mathematics
Spatial domain digital watermarking of multimedia objects for buyer authentication
IEEE Transactions on Multimedia
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
A wavelet visible difference predictor
IEEE Transactions on Image Processing
Improved wavelet-based watermarking through pixel-wise masking
IEEE Transactions on Image Processing
Robustness-set in watermarking embedding systems using codebook classifications
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
Grouping strategies for promoting image quality of watermarking on the basis of vector quantization
Journal of Visual Communication and Image Representation
A new digital image watermarking scheme based on Schur decomposition
Multimedia Tools and Applications
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The growth of the Internet has increased the phenomenon of digital piracy, in multimedia objects, like software, image, video, audio and text. Therefore it is strategic to individualize and to develop methods and numerical algorithms, which are stable and have low computational cost, that will allow us to find a solution to these problems. We describe a digital watermarking algorithm for color image protection and authenticity: robust, not blind, and wavelet-based. The use of Discrete Wavelet Transform is motivated by good time-frequency features and a good match with Human Visual System directives. These two combined elements are important for building an invisible and robust watermark. Moreover our algorithm can work with any image, thanks to the step of pre-processing of the image that includes resize techniques that adapt to the size of the original image for Wavelet transform. The watermark signal is calculated in correlation with the image features and statistic properties. In the detection step we apply a re-synchronization between the original and watermarked image according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has been shown to be resistant against geometric, filtering, and StirMark attacks with a low rate of false alarm.