scholarly journals Universal Decoding of Watermarks Under Geometric Attacks

Author(s):  
Pierre Moulin
Keyword(s):  
Author(s):  
Chauhan Usha ◽  
Singh Rajeev Kumar

Digital Watermarking is a technology, to facilitate the authentication, copyright protection and Security of digital media. The objective of developing a robust watermarking technique is to incorporate the maximum possible robustness without compromising with the transparency. Singular Value Decomposition (SVD) using Firefly Algorithm provides this objective of an optimal robust watermarking technique. Multiple scaling factors are used to embed the watermark image into the host by multiplying these scaling factors with the Singular Values (SV) of the host image. Firefly Algorithm is used to optimize the modified host image to achieve the highest possible robustness and transparency. This approach can significantly increase the quality of watermarked image and provide more robustness to the embedded watermark against various attacks such as noise, geometric attacks, filtering attacks etc.


2013 ◽  
Vol 33 (2) ◽  
pp. 434-437 ◽  
Author(s):  
Xinghong CHENG ◽  
Yuqing HOU ◽  
Jingxing CHENG ◽  
Xin PU

2013 ◽  
Vol 347-350 ◽  
pp. 3232-3236
Author(s):  
Zheng Bao Zhang ◽  
Chao Jia

Lots of anti-RST attacks watermarking algorithms have been proposed, but few solutions for local geometric attacks, in this paper it proposed a new algorithm combined with the the Wavelet Moment for an anti-geometric attacks. Since wavelet moment was proposed, it is widely used in the field of computer vision, image processing, but the large amount of computation must be improved to be applied to digital watermarking technology so that it can adapt to the real-time detection of digital watermarking. By image rotation, scaling, translation, shear, local distortions, filtering attack operations and so on, these attacks can be seen that the algorithm has good robustness, and the efficiency of watermark detection is relatively high. The experiments show that the algorithm is robustness, greatly accelerate the speed of operation, to unify the robust and efficient.


Author(s):  
Muhammad Tahir Naseem ◽  
Ijaz Mansoor Qureshi ◽  
Atta-ur-Rahman ◽  
Muhammad Zeeshan Muzaffar

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1377
Author(s):  
Qiumei Zheng ◽  
Nan Liu ◽  
Fenghua Wang

The discrete wavelet transform (DWT) is unable to represent the directional features of an image. Similarly, a fixed embedding strength is not able to establish an ideal balance between imperceptibility and robustness of a watermarked image. In this work, we propose an adaptive embedding strength watermarking algorithm based on shearlets’ capture directional features (S-AES). We improve the watermarking algorithm in the domain of DWT using non-subsampled shearlet transform (NSST). The improvement is made in terms of coping with anti-geometric attacks. The embedding strength is optimized by artificial bee colony (ABC) to achieve higher robustness under the premise of satisfying imperceptibility. The principle components (PC) of the watermark are embedded into the host image to overcome the false positive problem. The simulation results show that the proposed algorithm has better imperceptibility and strong robustness against multi-attacks, especially those of high intensity.


2018 ◽  
Vol 8 (12) ◽  
pp. 2617 ◽  
Author(s):  
Zhen Yue ◽  
Zichen Li ◽  
Hua Ren ◽  
Yixian Yang

The histogram watermark, which performs watermark embedding by slightly modifying the histogram of the original image, has been a hot research topic in information hiding technology due to the superiority of its pixel modification during the watermark embedding process, which is independent of the pixel position. This property makes the histogram-based watermark strong resistant to geometric attacks, such as cropping attack, crossed attack, rotation attack, etc. In this paper, we propose a large capacity histogram-based robust watermarking algorithm based on three consecutive bins for the first time. In our scheme, we divide the shape of three consecutive bins into eight cases. According to these cases, we embed Information Number 0, 1, 2, 3, 4, 5, 6, or 7, respectively. The embedded information capacity reaches one bit per bin (bpb), and the amount of embedded information is equal to 200% of the previous existing algorithms. Experimental results show that the new algorithm not only has a large capacity of embedding information, but also has strong robustness to geometric attacks, as well as common image processing operations.


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