scholarly journals Fast Watermark Synchronization Based on Complementary Templates

2014 ◽  
Vol 02 (04) ◽  
pp. 58-65
Author(s):  
Jong-Uk Hou ◽  
Sang-Keun Ji ◽  
Heung-Kyu Lee
Keyword(s):  
Watermark Synchronization

scholarly journals Screen-Cam Robust Image Watermarking with Feature-Based Synchronization

2020 ◽  
Vol 10 (21) ◽  
pp. 7494
Author(s):  
Weitong Chen ◽  
Na Ren ◽  
Changqing Zhu ◽  
Qifei Zhou ◽  
Tapio Seppänen ◽  
...  
Keyword(s):  
Image Watermarking ◽  
Gaussian Function ◽  
Geometric Distortion ◽  
Low Pass ◽  
Feature Based ◽  
Robust Image ◽  
Watermarking Scheme ◽  
Watermark Synchronization ◽  
Desynchronization Attacks ◽  
Traditional Image

The screen-cam process, which is taking pictures of the content displayed on a screen with mobile phones or cameras, is one of the main ways that image information is leaked. However, traditional image watermarking methods are not resilient to screen-cam processes with severe distortion. In this paper, a screen-cam robust watermarking scheme with a feature-based synchronization method is proposed. First, the distortions caused by the screen-cam process are investigated. These distortions can be summarized into the five categories of linear distortion, gamma tweaking, geometric distortion, noise attack, and low-pass filtering attack. Then, a local square feature region (LSFR) construction method based on a Gaussian function, modified Harris–Laplace detector, and speeded-up robust feature (SURF) orientation descriptor is developed for watermark synchronization. Next, the message is repeatedly embedded in each selected LSFR by an improved embedding algorithm, which employs a non-rotating embedding method and a preprocessing method, to modulate the discrete Fourier transform (DFT) coefficients. In the process of watermark detection, we fully utilize the captured information and extract the message based on a local statistical feature. Finally, the experimental results are presented to illustrate the effectiveness of the method against common attacks and screen-cam attacks. Compared to the previous schemes, our scheme has not only good robustness against screen-cam attack, but is also effective against screen-cam with additional common desynchronization attacks.

Estimating Digital Watermark Synchronization Signal Using Partial Pixel Least Squares

2020 ◽  
Vol 2020 (4) ◽  
pp. 24-1-24-7
Author(s):  
Robert Lyons ◽  
Brett Bradley
Keyword(s):  
Least Squares ◽  
Nearest Neighbor ◽  
Digital Watermark ◽  
Location Estimation ◽  
Fourier Frequency ◽  
Synchronization Signal ◽  
Linear Transform ◽  
Peak Location ◽  
Watermark Synchronization ◽  
Frequency Impulse

To read a digital watermark from printed images requires that the watermarking system read correctly after affine distortions. One way to recover from affine distortions is to add a synchronization signal in the Fourier frequency domain and use this synchronization signal to estimate the applied affine distortion. If the synchronization signal contains a collection of frequency impulses, then a least squares match of frequency impulse locations results in a reasonably accurate linear transform estimation. Nearest neighbor frequency impulse peak location estimation provides a good rough estimate for the linear transform, but a more accurate refinement of the least squares estimate is accomplished with partial pixel peak location estimates. In this paper we will show how to estimate peak locations to any desired accuracy using only the complex frequencies computed by the standard DFT. We will show that these improved peak location estimates result in a more accurate linear transform estimate. We conclude with an assessment of detector robustness that results from this improved linear transformation accuracy.

A Novel Watermarking Algorithm Based on SURF and SVD

2013 ◽  
Vol 303-306 ◽  
pp. 2117-2121 ◽  
Author(s):  
Wei Wang ◽  
Wen Hui Li ◽  
Cheng Xi Wang ◽  
Peng Wang
Keyword(s):  
Copyright Protection ◽  
Information Hiding ◽  
Singular Value ◽  
Geometric Distortion ◽  
Geometric Attacks ◽  
Speeded Up Robust Features ◽  
Key Points ◽  
Value Decomposition ◽  
Watermark Synchronization ◽  
Better Than

A novel watermarking algorithm based on SURF (Speeded Up Robust Features) and Singular Value Decomposition (SVD) is presented for copyright protection. By introducing the SURF’s key points matching and geometric distortion estimation, the attacked watermarked image can be corrected and the watermark synchronization is realized. In this way, the feature regions of the host image, which are used for information hiding, can be correctly detected by the improved Harris-Laplace corner detector even after signal processing and geometric attacks. The application of the proposed scheme makes the watermark capable of transparent hiding. Extensive experimental results demonstrate that our technique performs better than traditional methods under different attacks.

A Survey of Current Watermarking Synchronization Techniques

2011 ◽  
pp. 84-105
Author(s):  
Nataša Terzija
Keyword(s):  
Research And Development ◽  
Development Effort ◽  
Original Image ◽  
Image Content ◽  
Synchronization Process ◽  
Geometric Distortions ◽  
Watermark Embedding ◽  
The Subject ◽  
Watermark Synchronization

The resistance of watermarking schemes against geometric distortions has been the subject of much research and development effort in the last 10 years. This is due to the fact that even the minor geometric, manipulation of the watermarked image can dramatically reduce the ability of the watermark detector to detect the watermark, that is, the watermark detector can lose the synchronization. By this, the watermark synchronization can be defined as a process for finding the location for watermark embedding and detection. A variety of techniques have been proposed to provide partial robustness against geometrical distortions. These techniques can be divided into two groups: (1) techniques that use the original image to recover to synchronization and (2) techniques that do not have the access to the original image content during the synchronization process. This chapter classifies and analyzes techniques and approaches that are currently used in watermarking schemes to recover the synchronization.

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