Animation Zero Watermarking Algorithm Based on Edge Feature

Li, De; Yang, Shan; Zuo, YiAn; Zheng, Zhenrong; Cui, LiHua

doi:10.1007/978-981-13-1328-8_73

Cited by 4 publications

(7 citation statements)

References 4 publications

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“…(2) According to formula (12), permute the obtained binary sequence BS using the index ind C , and further rearrange it into a permuted binary matrix M F .…”

Section: Zero-watermark Generationmentioning

confidence: 99%

“…Li et al [10] obtained the key information of frames by DCT and DWT, and used log-polar transform (LPM) for confronting the rotation, so their method can stand up to rotation and frame switching attacks, but cannot resist other geometric attacks. In [12], Li et al introduced a zerowatermarking method by using the hybrid transforms of DCT, DWT and SVD, which can resist some common signal processing and framework-based attacks, but it only aims at cartoon image formed by using the method of grid by grid and continuous playback. In order to resist high-efficiency video coding compression (HEVC), Yu et al [33] presented a novel zero-watermarking method based on DWT, all phase biorthogonal transform (APBT) and SVD.…”

Section: Introductionmentioning

confidence: 99%

“…Despite the unceasing development of video zero-watermarking in recent years, there is still much room for improvement. For one thing, many zero-watermarking methods [10,12,15,30,33,34] only focus on the enhancement of the robustness, ignoring the research on the equalization and distinguishability of zero-watermark. Moreover, in the robustness evaluation, some methods [12,16,30] only concentrate on the study of intra-frame attacks and neglect the unique inter-frame attacks of video.…”

Section: Introductionmentioning

confidence: 99%

“…For one thing, many zero-watermarking methods [10,12,15,30,33,34] only focus on the enhancement of the robustness, ignoring the research on the equalization and distinguishability of zero-watermark. Moreover, in the robustness evaluation, some methods [12,16,30] only concentrate on the study of intra-frame attacks and neglect the unique inter-frame attacks of video. Based on the above analysis, the current challenge of video zero-watermark technology is how to extract the robust and distinguishable features of video content to construct zero-watermark.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A robust video zero-watermarking based on deep convolutional neural network and self-organizing map in polar complex exponential transform domain

Gao

Kang

Chen

2020

Multimed Tools Appl

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In this paper, a robust video zero-watermarking scheme for copyright protection using a combination of convolutional neural network (CNN) and self-organizing map (SOM) in polar complex exponential transform (PCET) space is presented. The scheme is developed not only to remedy the existing problems of lacking in some performance assessments but also to enhance the robustness. It starts with extracting the content feature of each frame by CNN and then some significant frames are selected using SOM clustering and maximum entropy. Secondly, the PCET is applied to all selected frames to abstract invariant moments, and further, is scrambled by a chaotic logistic map and is reduced in dimensions by singular value decomposition (SVD). Next, a binary sequence is generated by comparing adjacent values of the obtained compact PCET moments in the previous step, and further is permuted to produce a binary matrix. Finally, a bitwise exclusive-OR operation is imposed on the binary matrix and the encrypted watermark by the chaotic map to generate a zero-watermark signal. Experimental results demonstrate that the proposed scheme has adequate equalization and distinguishability of zero-watermarks as well as strong robustness against common signal processing, geometric, compression, and inter-frame attacks. Also, compared with existing video zero-watermarking and traditional video watermarking methods, the proposed scheme exhibits superior robustness.

show abstract

“…(2) According to formula (12), permute the obtained binary sequence BS using the index ind C , and further rearrange it into a permuted binary matrix M F .…”

Section: Zero-watermark Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A robust video zero-watermarking based on deep convolutional neural network and self-organizing map in polar complex exponential transform domain

Gao

Kang

Chen

2020

Multimed Tools Appl

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show abstract

“…This algorithm has weak resistance to cropping attacks. Based on the contour wave transform, the pseudo-3D DCT, and SVD, Li et al [22] proposed a zero-watermarking algorithm for copyright protection of animation videos. This algorithm is less robust to compression attacks and cut attacks.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Transforms-Based Robust Video Zero-Watermarking Algorithm for Resisting High Efficiency Video Coding Compression

Wang

Zhou

2019

IEEE Access

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With the rampancy of pirated videos, video watermarking for copyright protection has become a widely researched topic. In this paper, zero-watermarking is applied to videos for the first time to resist high efficiency video coding compression, which can improve the robustness of the watermarking algorithm and ensure the videos' quality. A robust video zero-watermarking algorithm based on the discrete wavelet transform, the all phase biorthogonal transform, and singular value decomposition is proposed. Utilizing the properties of hybrid transforms, robust features can be extracted from videos, and robust zero-watermarks can be constructed. Experimental results demonstrate that the proposed algorithm has strong robustness to high efficiency video coding compression attacks with different quantization parameters. In addition, the algorithm can also resist common image processing attacks, geometric attacks, frame-based attacks, and hybrid attacks. Compared with existing video watermarking algorithms, the proposed algorithm can more accurately and completely reconstruct watermark images.INDEX TERMS Video signal processing, watermarking, video watermarking, zero-watermarking, copyright protection, robustness, high efficiency video coding, discrete wavelet transform, all phase biorthogonal transform, singular value decomposition.

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A robust and secure zero-watermarking copyright authentication scheme based on visual cryptography and block G-H feature

Shi

et al. 2022

Multimed Tools Appl

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Animation Zero Watermarking Algorithm Based on Edge Feature

Cited by 4 publications

References 4 publications

A robust video zero-watermarking based on deep convolutional neural network and self-organizing map in polar complex exponential transform domain

A robust video zero-watermarking based on deep convolutional neural network and self-organizing map in polar complex exponential transform domain

A Hybrid Transforms-Based Robust Video Zero-Watermarking Algorithm for Resisting High Efficiency Video Coding Compression

A robust and secure zero-watermarking copyright authentication scheme based on visual cryptography and block G-H feature

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