Blind Video Watermarking Research Articles

Hide and track: Towards blind video watermarking network in frequency domain

Blind video watermarking (BVW) is the process of embedding visually imperceptible messages into a cover video, which can be retrieved even in the presence of distortion without requiring any reference to the original video. Compared to image watermarking, BVW encounters two critical challenges: 1) ensuring the visually imperceptible of the embedded information across sequential frames; 2) enabling quick localization of the watermarked frames in the event of temporal and spatial attacks such as frame dropping and video compression. This paper presents a robust blind video watermarking network by exploring a block-based selection mechanism in the frequency domain. The network comprises an encoding part that hides the watermark in a suitable location within the video to ensure visual imperceptibility of the watermark, and a decoding part that tracks the watermark in the frequency domain to ensure its robustness even when the video is distorted. Moreover, a plug-and-play watermark detector is designed to discover watermarking locations. This detector is readily applicable and can be easily integrated into most frequency watermarking embedding methods. Experimental results demonstrate that the proposed method outperforms the state-of-the-art methods on imperceptibility and robustness significantly. Our framework achieves an average peak signal-to-noise ratio (PSNR) of 37.59 dB and a Learned Perceptual Image Patch Similarity (LPIPS) of 1.12×10−2. Furthermore, the extraction accuracy reaches 99.99% under a variety of temporal attacks which demonstrates the robustness of the proposed method.

Robust Blind Video Watermarking Based on Ring Tensor and BCH Coding

Robust Blind Video Watermarking Based on Ring Tensor and BCH Coding

A Robust and Imperceptible Dark Frame Selection Using Advanced Squeezed Convoluted Ebola Neural Network-Based Video Watermarking Scheme with All Phase Discrete Cosine Biorthogonal Transform

Watermarking has been developed as a beneficial approach to resolve security problems such as copyright defense, legitimate ownership, and authenticity of digital data. Grayscale or binary images and color images are the most important types of embedded watermarks in the existing video watermarking schemes, while dark frame watermarking is barely used. A new robust blind video watermarking system with an Advanced Squeezed Convoluted Ebola Neural Network (ASCENN) approach is suggested to secure copyright, reduce noise, and authenticate the authenticity of dark frames. The proposed method selects the dark frames from the extracted input video. Then the selected dark frames are embedded and extracted using Finite Ridgelet Transform (FRT), All Phase Discrete Cosine Biorthogonal Transform (APDCBT), and Singular Value Decomposition (SVD) techniques. The robustness of the introduced approach is established by evaluating it through various image watermarking techniques and evaluating its performance against geometric, nongeometric, and combinational attacks. While comparing with the other existing video watermarking approaches, the proposed method has obtained a maximum correlation coefficient of 1, and the signal-to-noise ratio of 75[Formula: see text]dB, at minimum error rate of 0.0215, respectively.

Blind video watermarking scheme for medical video authentication

Medical video watermarking is one of the beneficial and efficient tools to prohibit important patients' data from illicit enrollment and redistribution. In this paper, a new blind watermarking scheme has been proposed to improve the confidentiality, integrity, authenticity, and perceptual quality of a medical video with minimum distortion. The proposed scheme is based on 2D-DWT and dual Hessenberg-QR decomposition, where the input medical video is initially processed into frames. Then, the processed frames are transformed into sub-bands using 2D-DWT, followed by applying Hessenberg-QR decomposition on the selected wavelet HL2 sub-band. The watermark is scrambled via Arnold cat map to raise confidentiality and then concealed in the modified selected features. The watermark is extracted in a fully blind mode without referencing the original video, which reduces the extraction time. The proposed scheme maintained a fundamental tradeoff between robustness and visual imperceptibility compared to existing methods against many commonly encountered attacks. The visual imperceptibility has been evaluated using well-known metrics PSNR, SSIM, Q-index, and histogram analysis. The proposed scheme achieves a high PSNR value of (70.6899 dB) with minimal distortion and a high robustness level with an average NC value of (0.9998) and BER value of (0.0023) while conserving a large payload capacity. The obtained results show superior performance over similar video watermarking methods. The limitation of this scheme is the elapsed time during the embedding process since we utilized dual Hessenberg-QR decomposition. One possible solution to reduce time consumption is simple decompositions like bound-constrained SVM or similar decompositions.

RSVD for Three Quaternion Tensors with Applications in Color Video Watermark Processing

In this paper, we study the restricted singular-value decomposition (RSVD) for three quaternion tensors under the Einstein product, and give higher-order RSVD over the quaternion algebra, which can achieve simultaneous singular value decomposition of three quaternion tensors. Moreover, we give the algorithm for computing the RSVD of for quaternion tensors. What is more, we present a new blind color video watermarking scheme based on the forth-order RSVD over the quaternion algebra, and our numerical example demonstrates the effectiveness of the framework.

Blind Camcording-Resistant Video Watermarking in the DTCWT and SVD Domain

Video watermarking techniques can be used to prevent unauthorized users from illegally distributing videos across (social) media networks. However, current watermarking solutions are unable to embed a perceptually invisible watermark which is robust to the distortions introduced by camcording. These watermark-disrupting distortions include lossy compression, the addition of noise, frame-rate conversion and geometric distortions. In this paper, we present a novel video watermarking technique that is blind and robust to camcording attacks. The proposed approach uses the integration of the dual-tree complex wavelet transform (DTCWT) and singular value decomposition (SVD) to achieve robustness against geometric attacks. The experimental results validate our technique’s superior imperceptibility and robustness to several attacks when compared to existing peer mechanisms. In conclusion, the proposed technique can be used to protect against illegal distribution of video content.

A new video watermarking using redundant discrete wavelet in singular value decomposition domain with multi‐objective optimization

AbstractDay by day, the transmission or sharing of digital information online is increasing due to the fact that Internet usage has become somewhat of an addiction for the majority of people. This results in larger copyright violation problems. Nowadays, most of the data or information is being transmitted in the form of digital images or videos, which are rather simple for the violators of copyright to forge or fake and then share for profit. Thus, digital watermarking came into existence as a possible solution to address these violations of copyright. This article proposes a new blind video watermarking (BVW) using redundant discrete wavelet transform (RDWT) in singular value decomposition (SVD) domain, which utilizes the advantages of both RDWT and SVD to embed and extract the watermark information into the cover video without degrading the quality of the watermark. In addition, an efficient meta‐heuristic optimization with multi‐objective optimization (MOO) is employed to further optimize the proposed RDWT‐SVD approach. Further, various attacks were applied to the watermarked frame to disclose the robustness of proposed BVW using RDWT‐SVD with MOO approach. Extensive simulations on several test videos with comparison to the conventional BVW methodologies exhibit the transcendency of the proposed BVW using RDWT‐SVD with MOO approach in terms of watermarking quality evaluation metrics such as peak signal‐to‐noise ratio (PSNR), structural similarity index, normalized correlation, and even that of root mean square error as well.

A Robust DWT-Based Compressed Domain Video Watermarking Technique

To achieve robustness and imperceptibility, an adaptive compressed domain blind video watermarking method based on Discrete Wavelet Transform (DWT) is proposed in this research. In this technique, multiple binary images derived from a single watermark image are first embedded in a video sequence. The spatial spread spectrum watermark is directly incorporated in the compressed bit streams by modifying the four sets of discrete wavelet coefficients. Comprehensive simulation experiments demonstrate that the developed approach is efficient and also robust against spatial attacks such as scaling and frame averaging, noise attacks such as Gaussian and salt pepper noise, and temporal attacks like frame dropping and shifting. Moreover, the proposed approach can also withstand against rotation attacks of arbitrary angle.

A blind video watermarking algorithm robust to lossy video compression attacks based on generalized Newton complex map and contourlet transform

The rapid growth of fast communication networks for digital video transmission has created a need to copyright protection for these media. Digital video can be manipulated easily by users with various motivations. Compression is the most common attack that users can apply on videos in order to eliminate digital video copyright. Proposed technique in this article is specially designed for resisting against compression attacks. This method is presented a blind and robust watermarking method to copyright protection in digital video. In the proposed method, the coefficients of the contourlet transform are extracted and then encrypted watermark embedded into video with using the singular value decomposition (SVD). Embedding watermark in SVD domain increases the robustness of proposed method against attacks. In the embedding process and watermark encryption, pseudo-random numbers generated by the proposed new chaotic map, which is a generalized two-dimensional complex map based on the Newton model. The PSNR, SSIM, BER, and NCC measures examine the performance of the proposed method in terms of robustness and visual quality.

Efficient Security Base d Video Watermarking Technique u sing Chaotic Encryption with Discrete Cosine Transform

In this paper, a novel chaotic encryption-based blind digital video watermarking technique (DVWT) is presented for grayscale and color images. This method makes use of Discrete Cosine transform (DCT) prior to embed the watermark in the hosting video. The hosting video is split into frames of 8*8 nonoverlapping blocks before employing DCT, and watermark bit is implanted by altering the variations among the nearby DCT coefficients of neighboring blocks. Arnold transform is applied for chaotic encryption to offer extra security to the watermark. A set of three versions of the proposed model has been applied and the results are investigated. The experimental outcome confirms that the DCT-VWT is efficient on different image processing functions such as JPEG compression, sharpening, cropping, and median filtering. The comparative analysis ensures that the presented DCT for digital video watermarking technique (DCT-DVWT) is efficient under subjective as well as objective way.

Robust compressed domain watermarking algorithm for video protection and authentication in noisy channels

This paper introduces a robust and noise-resilient compressed domain video watermarking technique for data authentication and copyright protection. In recent years, watermarking has emerged as an essential technique to be equipped with data transmission. The main challenge pertaining to transmission is to protect the watermark from noise introduced by the channel. Here, we address this issue by watermark replication and by using the independent pass coding (INPAC) algorithm for compression. A replicated watermark is embedded into the video by the proposed blind video watermarking algorithm and then the watermarked video is compressed by the INPAC algorithm. The compressed video is transmitted through binary symmetric channels and tested under various bit error rates to evaluate the proposed algorithm in noisy environments. The results obtained suggest that the proposed algorithm is capable of handling noise efficiently and the overhead due to key embedding is observed to be only about 3%.

A video watermark algorithm based on tensor decomposition.

Since most of the previous video watermark algorithms regard a video as a series of consecutive images, the embedding and extraction of watermark are performed on these images, and the correlation and redundancy among frames of a video are not considered. Such algorithms are weak in protecting against frame attacks. In order to improve the robustness, we take into consideration the correlation and redundancy among the frames of a video to propose a blind video watermark algorithm based on tensor decomposition. First, a grayscale video is represented as a 3-order tensor, and the core tensor is obtained by tensor decomposition. Second, the watermark embedding position is selected based on the stability of the maximum value in the core tensor because the core tensor represents the main energy of a video. Then, the watermark is embedded by quantifying the maximum value in the core tensor. Finally, the watermark is uniformly distributed across frames of a video by inverse tensor decomposition. The experiments show that our algorithm based on tensor decomposition has better imperceptibility and robustness against common video attacks.

A fast video watermarking algorithm using dual tree complex wavelet transform

Illegal camcording as the most common source of video piracy, is the main concern of the film production companies. With the increased speed and convenience of access to the Internet and video sharing services, the distribution of pirated video copies is more than easy. Digital video watermarking is one of the possible ways to prevent the illegal recording and distribution of videos. In this paper, a blind digital video watermarking method based on Dual-Tree Complex Wavelet Transform (DTCWT) is proposed. Here, the generated watermark is embedded in the low frequency coefficients of the chrominance channel of the video frames. The watermark is generated in a way that the detection system does not need to know the size of the original video. To reduce the computational complexity of the proposed method, the embedding process is equivalently done in the spatial domain. The proposed method is compared to the state-of-art methods against different attacks. Experimental results show that the proposed method is more robust against various attacks while maintaining the perceptual quality of the original video significantly better than the compared methods. Also the proposed method is evaluated in terms of computational complexity which reveals that the proposed method performs faster than the compared methods.

A Novel Blind and Robust Video Watermarking Technique in Fast Motion Frames Based on SVD and MR-SVD

In this work, a novel and efficient digital video watermarking technique based on the Singular Value Decomposition performed in the Multiresolution Singular Value Decomposition domain is proposed. While most of the existing watermarking schemes embed the watermark in all the video frames, which is time-consuming and also affects the perceptibly of the video quality, the proposed method chooses only the fast motion frames in each shot to host the watermark. In doing so, the number of frames to be processed is consequently reduced and a better quality of the watermarked video is also ensured since the human visual system cannot notice the variations in fast moving regions. The watermark information is embedded by Quantization Index Modulation which is a blind watermarking algorithm. The experimental results demonstrate that the proposed method can achieve a very good transparency, while being robust against various kinds of attacks such as filtering, noising, compression, and frame collusion. Compared with several methods found in the literature, the proposed method gives a better robustness.

A multiplicative video watermarking robust to H.264/AVC compression standard

The widespread application of the H.264 video compression standard necessitates proper design of copyright protection algorithms. In this paper, a new blind multiplicative video watermarking algorithm robust to this standard and also other attacks is proposed. With this method, the multiplicative watermark is embedded in the HH subband of the wavelet-transformed video frames. The HH coefficients of the host signal are divided into two patches: One patch is used to host the watermark, while the other patch is remained intact to be exploited at the receiver for estimating the system parameters required for watermark detection. Assuming the wavelet HH coefficients to have the Laplacian distribution, the maximum likelihood (ML) criterion is used for the watermark detection. In this case, the ratio of summation of samples of two patches is used as our decision variable on which the ML criterion is applied. Simulation results show that along with the exhibition of an acceptable robustness against various attacks, the proposed algorithm properly satisfies the invisibility requirements of the watermarking concept with low computational complexity.

A blind and robust video watermarking based on IWT and new 3D generalized chaotic sine map

In the modern world, high-bandwidth internet access has led to the theft of all types of digital data, including digital video, and their illegal distribution. The digital video watermarking technique was introduced late last century to enforce video copyright protection. In this paper, a robust blind and secure video watermarking method is presented based on integer wavelet transform and the generalized chaotic sine map. In this method, integer wavelet transform is applied to each main frame of the standard video. Basically, watermarking techniques are evaluated based on three concepts of content quality, data resilience and data capacity. Therefore, in order to guarantee the quality of the watermarked video, the watermark is inserted in low-frequency coefficients. An appropriate security level is added to increase the efficiency and functionality by chaotic map to watermark. In addition, the normalized correlation coefficient (NCC) between the main watermark and extraction watermark is used as the main criterion of resistance measurement. The results show that the proposed method is good in terms of both quality and resistance to a variety of attacks, and the NCC values obtained in most cases are 1 or very close to 1.

Performance analysis of 2 level DWT-SVD based non blind and blind video watermarking using range conversion method

The recent availability of inexpensive digital recording and storage devices have created an environment to obtain, replicate and distribute digital content without any loss in quality. Hence copyright protection and authentication have become inevitable. Leading to a need, to develop an efficient scheme for video watermarking, involving 2-level discrete wavelet transform (DWT) and proficient decomposition technique of singular value decomposition (SVD). Performance parameters like processing time, peak signal to noise ratio (PSNR) and normalized correlation (NC) are compared for non-blind and blind watermarking techniques. Focusing the PSNR and NC values are obtained as an average value of 40 dB and 0.99 respectively, when subjected to formidable noise attacks such as geometrical, filtering, salt and pepper noises. Range conversion method improves PSNR for challenging attacks like salt and pepper, Gaussian and Gamma noises.

A Copyright Protection Scheme for Videos Based on the SIFT

A blind and robust video watermarking algorithm for copyright protection of the videos in the discrete wavelet transform is proposed in this paper. Each frame of the video is decomposed and binary watermark bit is embedded in high frequency coefficients. For better security, the watermark is encrypted prior to embedding using the cat map. Scale invariant feature transform is used to restore against the rotation attack. Two pairs of matched feature points from the original watermarked frames and corresponding attacked frames are used to find the angle of rotation angle against rotation attack. Experimental results show the imperceptibility and robustness of the proposed method against a variety of attacks. It is especially robust against rotation attack in comparison with other popular watermarking methods.

Video Watermarking Scheme based on IDR frames using MPEG-2 Structure

A robust, imperceptible and blind video watermarking scheme based on MPEG-2 is presented. The proposed algorithm using the DC coefficients from 8 × 8 block of discrete coefficient transform generated by picking candidate IDR frames based on column transposition method in order to embed the scrambled binary watermark. The watermark can only be extracted by using the secret keys, enhances the security of watermark. The robustness is evaluated by testing against spatial synchronisation attacks, temporal synchronisation attacks and re-encoding attacks by evaluating two parameters as normalised correlation and bit error rate in order to find the degree of similarity and degree of dissimilarity respectively between the original and extracted watermark. The superiority of the proposed algorithm is that the excellent robustness achieved against temporal synchronisation attacks and compression attack by comparing it with previous work and also good perceptibility obtained without changing the motion vectors during the DPCM process of MPEG-2 encoding scheme.

Study of wavelets using chaotic map on DWT based blind video watermarking

Study of wavelets using chaotic map on DWT based blind video watermarking