Digital watermarking based on neural networks for color images
Signal Processing - Special section on digital signal processing for multimedia communications and services
A public verifiable copy protection technique for still images
Journal of Systems and Software
Adaptive watermark mechanism for rightful ownership protection
Journal of Systems and Software
A robust watermarking scheme using self-reference image
Computer Standards & Interfaces
DCT-based image watermarking using subsampling
IEEE Transactions on Multimedia
Joint wavelet and spatial transformation for digital watermarking
IEEE Transactions on Consumer Electronics
A robust DCT-based watermarking for copyright protection
IEEE Transactions on Consumer Electronics
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
Hidden digital watermarks in images
IEEE Transactions on Image Processing
Improved wavelet-based watermarking through pixel-wise masking
IEEE Transactions on Image Processing
Multipurpose image watermarking algorithm based on multistage vector quantization
IEEE Transactions on Image Processing
Embedding image watermarks in dc components
IEEE Transactions on Circuits and Systems for Video Technology
Fuzzy-ART based adaptive digital watermarking scheme
IEEE Transactions on Circuits and Systems for Video Technology
Image watermarking method in multiwavelet domain based on support vector machines
Journal of Systems and Software
Intelligent reversible watermarking in integer wavelet domain for medical images
Journal of Systems and Software
A robust zero-watermarking scheme using Canny edge detector
International Journal of Electronic Security and Digital Forensics
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Protecting the intellectual property rights (IPR) of digital media is important because the illegal reproduction and modification of digital media has become increasingly serious. A robust DWT-based copyright verification scheme with Fuzzy ART that does not require the original image for ownership verification is proposed in this paper. The proposed scheme, which combines DWT, Fuzzy ART, and the quantization process, converts an image into a short robust table with the embedded ownership information. Unlike general classification, such as k-mean and fuzzy c-means, the number of clusters can be adaptively decided by the vigilance parameter of Fuzzy ART. Experimental results demonstrate that the proposed scheme is robust against common image processing, geometric distortions, and intentional attacks. The original image is not required to extract the embedded ownership image.