A blind watermarking algorithm based on DWT and SVD

This paper presents a new digital image blind watermarking algorithm based on combination of discrete wavelet transform （DWT） and singular value decomposition （SVD）. First of all, we make wavelet decomposition for the original image and divide the acquired low frequency sub-band into blocks. Then we make singular value decomposition for each block and embed the watermark information in the largest singular value by quantitative method. The watermark can be extracted without the original image. The experimental results show that the algorithm has a good imperceptibility and robustness.

Robust blind image watermarking based on interest points

Digital watermarking technology plays an essential role in the work of anti-counterfeiting and traceability.However,image watermarking algorithms are weak against hybrid attacks,especially geometric attacks,such as cropping attacks,rotation attacks,etc.We propose a robust blind image watermarking algorithm that combines stable interest points and deep learning networks to improve the robustness of the watermarking algorithm further.First,to extract more sparse and stable interest points,we use the Superpoint algorithm for generation and design two steps to perform the screening procedure.We first keep the points with the highest possibility in a given region to ensure the sparsity of the points and then filter the robust interest points by hybrid attacks to ensure high stability.The message is embedded in sub-blocks centered on stable interest points using a deep learning-based framework.Different kinds of attacks and simulated noise are added to the adversarial training to guarantee the robustness of embedded blocks.We use the ConvNext network for watermark extraction and determine the division threshold based on the decoded values of the unembedded sub-blocks.Through extensive experimental results,we demonstrate that our proposed algorithm can improve the accuracy of the network in extracting information while ensuring high invisibility between the embedded image and the original cover image.Comparison with previous SOTA work reveals that our algorithm can achieve better visual and numerical results on hybrid and geometric attacks.

A blind watermarking algorithm for 3D mesh models based on vertex curvature

We propose a robust blind watermarking algorithm for three-dimensional(3D)mesh models based on vertex curvature to maintain good robustness and improve visual masking in 3D mesh models.In the embedding process,by using the local window of vertex,the root mean square curvature is calculated for every vertex of the 3D mesh model and an ordered set of fluctuation values is obtained.According to the ordered fluctuation values,the vertices are separated into bins.In each bin the fluctuation values are normalized.Finally,the mean of the root mean square curvature fluctuation values of the vertices in each bin is modulated to embed watermark information.In watermark detection,the algorithm uses a blind watermark extraction technique to extract the watermark information.The experimental results show that the algorithm has a very good performance for visual masking of the embedded model and that it can resist a variety of common attacks such as vertex rearrangement,rotation,translating,uniform scaling,noise,smoothing,quantization,and simplification.

A Blind Watermarking Algorithm Resisting to Geometric Transforms Based on SVD

A new watermarking algorithm resisting to geometric transformation based on singular value decomposition （SVD） in logarithm polar coordinate is proposed. The log-polar mapping （LPM） is used to resist rotation and scaling attacks, and the odd-even quantization algorithm is used to embed watermark so it can be extracted without the original host image. The experiments show that the proposed algorithm not only resists various geomet- ric attacks but also is robust enough to the common signal processing.

Hybrid Successive CFA Image Encryption-Watermarking Algorithm Based on the Quaternionic Wavelet Transform (QWT)

In this paper, we present a new robust hybrid algorithm combining successively chaotic encryption and blind watermarking of images based on the quaternionic wavelet transform (QWT) to ensure the secure transfer of digital data. The calculations of the different evaluation parameters have been performed in order to determine the robustness of our algorithm to certain attacks. The application of this hybrid algorithm on CFA (Color Filter Array) images, allowed us to guarantee the integrity of the digital data and to propose an autonomous transmission system. The results obtained after simulation of this successive hybrid algorithm of chaotic encryption and then blind watermarking are appreciated through the values of the evaluation parameters which are the peak signal-to-noise ratio (PSNR) and the correlation coefficient (CC), and by the visual observation of the extracted watermarks before and after attacks. The values of these parameters show that this successive hybrid algorithm is robust against some conventional attacks.

A New Robust Watermarking Algorithm for Vector Data

Because the existing vector data watermarking algorithm is insufficiently robust for compression and cropping,and has no sufficient control on map deformation,a new watermarking algorithm was proposed in this paper.Its main features are：① it selected feature points and non-feature points from the sequence of Douglas,and then embedded watermarking points by wavelet transform,which is based on layer segmentation;② it enhanced the map deformation control design.Furthermore,it increased the map graphic deformation control design.The algorithm was applied to experimental data,and the test results showed that the algorithm had good robustness on graphics geometric transformation,the addition,deletion and cropping of points in graph layers.Also,the graph distortion had been well controlled.