Blind Wavelet-based Image Watermarking Based on HVS and Neural Networks
Hung-Hsu Tsai 0, Chi-Chih Liu, Kuo-Chun Wang
0Dept. of Information Management, National Formosa University
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- https://doi.org/10.2991/jcis.2006.40How to use a DOI?
- Image Watermarking, Human Visual System, Neural Networks, Wavelets, Image Authorization
- This work proposes a Blind Wavelet-based Image Watermarking (BWIW) technique, based on the human visible system (HVS) model and neural networks, for image copyright protection. A characteristic of the HVS, the Just Noticeable Difference (JND) profile, is employed in the watermark embedding so that the BWIW technique can make the watermark further imperceptible. The technique is developed in the wavelet domain. While embedding a watermark in an image, it adds the adaptive strengths to the wavelet coefficients of the image according to the JND thresholds. Moreover, an artificial neural network (ANN) is used to memorize the relationships between the wavelet version of an original image and its watermarked image. An advantage of the BWIW technique is that it utilizes the trained ANN to estimate the watermark without the original image to be applied in the calculation of the JND profile of the image. Finally, computer simulations demonstrate that both the transparency and the robustness of the BWIW technique are better than that of other proposed methods.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Hung-Hsu Tsai AU - Chi-Chih Liu AU - Kuo-Chun Wang PY - NaN/NaN DA - NaN/NaN TI - Blind Wavelet-based Image Watermarking Based on HVS and Neural Networks BT - 9th Joint International Conference on Information Sciences (JCIS-06) PB - Atlantis Press UR - https://doi.org/10.2991/jcis.2006.40 DO - https://doi.org/10.2991/jcis.2006.40 ID - TsaiNaN/NaN ER -