Video Watermarking Research Articles

Systematic comparison of digital video watermarking aspects with techniques and algorithm designing issue

With the coming of innovation, verification and security have turned into the principle perspective during communication over the enormous distance. Unlawful dispersal of digital video is the principal peril to the entertainment world. With the advancement of web access, copied duplicates of digitized video might be essentially scattered to globalized watchers. A few applications of video watermarking in copyright insurance, security, fingerprinting, duplicate control, and comment are tremendously expanding. Consequently, a likely technique for confining such sort of digitalized theft is Digital Video Watermarking. At present, watermarking has arisen as a huge strategy to recognize the legitimacy and validation of the proprietor and to ensure the copyrights. The watermarking approach is used by the analysts to hide the secret data that might be apparent or dark according to the client’s need. This paper will outfit the disparate tendencies continued in the space of digital watermarking. Also, a point by point outline of digital video watermarking and writing review is talked about in an even arrangement which can give the bearings to forthcoming scientists to seek after their research in this field.

Robust Blind Video Watermarking Based on Ring Tensor and BCH Coding

Robust Blind Video Watermarking Based on Ring Tensor and BCH Coding

An improved video watermarking algorithm with extraction using a mobile device camera

The use of screen-capture-resistant digital watermarks is a promising way to store information invisibly in a video stream for later retrieval by the user using a smartphone camera. However, the development of algorithms that implement this scenario is associated with the problem of balancing between the imperceptibility of embedding and robustness. A serious problem is the extraction of watermarks using a mobile device. Most people use the vertical positioning of the smartphone when shooting, which excludes the possibility of only marked video sequences entering the frame. The extraction algorithm first finds the screen area in the image and then extracts the watermark under various distortion conditions. This study proposes an approach to improve the efficiency of the algorithm for embedding digital watermarks into video data based on rectangular patterns, which provides resistance to screen shooting. The proposed approach to increasing the embedding imperceptibility provided an increase in the PSNR and SSIM values by 17.18 % and 7.90 %, respectively. The use of a neural network at the extraction stage reduced the BER value by 64.64 %.

A Fast Method for Robust Video Watermarking Based on Zernike Moments

Watermarking by Zernike moments has been proven to be effective in providing high rotational resistance. However, due to the high computational complexity, the conventional video watermarking methods using Zernike moments are developed for videos with low resolution. Moreover, according to the properties of Zernike moments, only the matrices of equal height and width can be calculated since the inscribed circle of the original image matrix is selected as the area to be processed, but most of the available videos on the Internet do not meet such requirement. To solve the above problem, this paper proposes a fast watermarking method based on Zernike moments for high resolution videos to resist various attacks. In the proposed method, the frames of a video sequence are firstly grouped, from which a certain number of frame pairs are then selected for watermark embedding. For each frame pair to be embedded, we partition one frame into a set of disjoint blocks and apply singular value decomposition to each block to obtain a square feature matrix. Thereafter, by calculating all the Zernike moments, secret information is embedded into the selected Zernike moments to achieve superior robustness while keeping imperceptibility. Finally, according to the video encoding framework, we overwrite the frame difference of the frame pair by the watermark to resist compression and transcoding attacks. Furthermore, we propose two optional methods for compensating the special cases of rotation and scaling attacks during watermark detection. Experiments demonstrate the advantage of our method over the existing robust watermarking methods.

Multipurpose video watermarking algorithm for copyright protection and tamper detection

Multipurpose video watermarking algorithm for copyright protection and tamper detection

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.

3D Video watermarking for MVD based view-synthesis and RST attack

3D Video watermarking for MVD based view-synthesis and RST attack

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.

Non-redundant shift-invariant complex wavelet transform and fractional gorilla troops optimization-based deep convolutional neural network for video watermarking

With the development of multimedia processing approaches along with the Internet leads to various issues, like data tampering, data piracy, and illicit dissemination. The quick progression of fast communication networks for digital video transmission has formulated the prerequisite copyright protection for these media. On the other hand, the development of Internet technologies has directed the accessibility of images, audio, and videos in different structures. Moreover, unlicensed users manipulate the utilization of multimedia by broadcasting them on numerous internet sites to get money fraudulently without the involvement of the original copyright holder. Besides, watermarking is a process utilized to hide the watermark sign present in the multimedia statistics that are not perceptible to an intruder for manipulating any information. This paper devised a novel video watermarking technique which uses an optimized deep learning technique. Here, the binary pixel map generation is performed using DCNN for self-embedding in input video. In addition, weights as well as bias of DCNN are trained by designed Fractional Gorilla Troops Optimization-Deep Convolutional Neural Network algorithm, thus FGTO_DCNN algorithm is developed. Accordingly, the FGTO technique is newly introduced by integrating FC along with GTO algorithm. Moreover, non-redundant Shift Invariant Complex Wavelet Transform (SICWT) is employed for extracted key frame and thus watermark image is fed into embedding process. After that, inverse non-redundant SICWT is applied for embedding video, which is further passed to key frame extraction in extraction stage. Finally, non-redundant SICWT is utilized for obtaining extracted watermark image. The developed FGTO-driven DCNN model attained improved performance than other existing video watermarking techniques with Mean Square Error (MSE) of 0.0437, Normalized Correlation Coefficient (NCC) of 0.9998, high Peak Signal-to-Noise Ratio (PSNR) value of 51.93 dB, and high Weighted Signal-to-Noise Ratio (WSNR) of 49.86 dB.

An Overview of Robust Video Watermarking Techniques

Copyright hacking and piracy have increased as the Internet has grown in popularity and access to multimedia material has increased. Security, property protection, and authentication have all been achieved via watermarking techniques. This paper presents a summary of some recent efforts on video watermarking techniques, with an emphasis on studies from 2018 to 2022, as well as the various approaches, achievements, and attacks utilized as testing measures against these watermarking systems. According to the findings of this study, frequency-domain watermarking techniques are more popular and reliable than spatial domain watermarking approaches. Hybrid DCT and DWT are the two most used techniques and achieve good results in the field of video watermarking, and the system is more robust against attacks. PSNR was taken into consideration as a comparison metric in various recent articles in terms of robustness in the video watermarking field.

A Robust Video Watermarking Algorithm Based on Two-Dimensional Discrete Fourier Transform

Due to the continuous development and popularity of digital video technology, the copyright protection of digital video content has become an increasingly prominent issue. Digital video watermarking, as an effective means of digital copyright protection, has attracted widespread attention from academia and industry. The two-dimensional discrete Fourier transform (2D-DFT) template-based method has the advantages of good real-time performance and robustness, but the embedding capacity is small and cannot resist frame-dropping attack. To address this problem, a new template construction method is proposed in this paper, which can extend the embedding capacity from 1 bit each group of pictures (GOP) to theoretically n bits each GOP. In addition, by changing the GOP pattern, the method gains the ability to resist frame-dropping attacks. Experimental results show that the proposed method can achieve larger watermark capacity while maintaining strong robustness against image-processing attacks, geometric attacks, video-processing attacks and compression attacks.

A new efficient anaglyph 3D image and video watermarking technique minimizing generation deficiencies

A new efficient anaglyph 3D image and video watermarking technique minimizing generation deficiencies

Anti-Recompression Video Watermarking Algorithm Based on H.264/AVC

The problem of information security and copyright protection of video is becoming increasingly prominent. The current video watermarking algorithm does not have strong anti-compression, which has a significant impact on the visual effect of video. To solve this problem, this paper proposes a video watermarking algorithm based on H.264/AVC. The algorithm combines the non-zero quantization coefficient and the energy factor to select the appropriate chroma subblock, and then an optimized modulation is designed to embed the watermark into its DCT quantization coefficients in order to minimize the number of modifications of the subblocks. The invisibility and robustness experiments of the algorithm are conducted in the paper, and the Structural Similarity Indexes are above 0.99, and the False Bit Rates are all below 0.03. The results show that the algorithm has good invisibility, anti-compression performance and obvious advantages compared with other similar methods.

Time-Domain Video Watermarking Algorithm for Data Security and Content Authentication

Abstract: Video watermarking is an essential method employed to invisibly and reliably incorporate information into digital videos. Its primary purposes include copyright protection, content authentication, and ownership verification. With the increasing prevalence of digital media and the ease of video sharing online, safeguarding intellectual property rights and ensuring video content integrity have become crucial. Video watermarking is an essential method employed to invisibly and reliably incorporate information into digital videos. Its primary purposes include copyright protection, content authentication, and ownership verification. With the increasing prevalence of digital media and the ease of video sharing online, safeguarding intellectual property rights and ensuring video content integrity have become crucial. Robustness is a crucial aspect of video watermarking, as watermarked videos may be subjected to various attacks or modifications. Robust video watermarking techniques employ error correction codes, spread spectrum modulation, or cryptographic algorithms to ensure the resilience of watermarks against attacks such as compression, filtering, and geometric transformations. Various aspects and performance characteristics must be taken into account while developing an algorithm. It is necessary to evaluate performance indicators like NCC, PSNR, BER, WER, SSIM, VIFP, VMAF, and many more.

Robust Video Watermarking Algorithm based on DCT-SVD approach and Encryption

Sharing of digital media content over the internet is increasing everyday .Digital watermarking is a technique used to protect the intellectual property rights of multimedia content owners. In this paper, we propose a robust video watermarking scheme that utilizes Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) for embedding a watermark into video frames. The proposed method uses encryption to make the watermark more robust against malicious attacks. The encryption key is used to modify the watermark before it is embedded in the video frames. The modified watermark is then embedded in the DCT and SVD coefficients of the video frames. The experimental results show that the proposed method provides better robustness against various attacks such as compression, noise addition, and filtering, while maintaining good perceptual quality of the watermarked video. The proposed method also shows better resistance against geometric attacks such as cropping, rotation, and scaling. Overall, the proposed method provides an effective solution for protecting the intellectual property rights of multimedia content owners in video distribution and transmission scenarios.

Video Copyright Protection

Illegal distribution of digital data is a common danger in the film industry, especially with the rapid spread of the Internet, where it is now possible to easily distribute pirated copies of digital video on a global scale. The Watermarking system inserts invisible signs to the video content without changing the content itself. The aim of this paper is to build an invisible video watermarking system with high imperceptibility. Firstly, the watermark is confused by using the Arnold transform and then dividing into equal, non-overlapping blocks. Each block is then embedded in a specific frame using the Discrete Wavelet Transform (DWT), where the HL band is used for this purpose. Regarding the method of selecting the host frames, the chaotic map (tent map) was used to choose a number of frames which are greater or equal to the number of blocks of the watermark. The host frame selection method makes the discovery of the watermark information by illegal means very complicated. The experimental results show that the proposed method can produce excellent transparency with robustness against some attacks where the average_ PSNR reaches to 72.806.

A Novel Method of Invisible Video Watermarking Based on Index Mapping and Hybrid DWT-DCT

Watermarking is widely used in multimedia preservation and communication, which comprises, and is therefore not limited to, data security and validation. Security, readability, imperceptibility, and resilience are some of the key advantages of this technology. However, there are still certain issues that need to be addressed, such as the ability to withstand a variety of assaults without substantially affecting the quality and value of embedded data. Based on its operational domain, the watermarking technology may be divided into two groups: spatial and frequency watermarking. An index mapping-based watermarking approach for copyright protection of multi-media color videos is presented in this paper. We offer a hybrid discrete wavelet transform and discrete cosine transform (DCT) watermarking algorithm for digital video watermarking of a color video watermark. Peak signal to noise ratio (PSNR), similarity structure index measure (SSIM), have been used to analyze the distortion produced by watermarking. It is suggested that the proposed video watermarking method provides greater imperceptibility in conjunction with each other with the human visual system and it offers higher robustness against different attacks.

The Most Common Characteristics of Fragile Video Watermarking

The progress of network and multimedia technologies has been phenomenal during the previous two decades. Unauthorized users will be able to copy, retransmit, modify reproduction, and upload the contents more easily as a result of this innovation. Malicious attackers are quite concerned about the development and widespread use of digital video. Digital watermarking technology gives solutions to the aforementioned problems. Watermarking methods can alleviate these issues by embedding a secret watermark in the original host data, allowing the genuine user or file owner to identify any manipulation. In this study, lots of papers have been analyzed and studied carefully, in the period 2011–2022. The historical basis of the subject should not be forgotten so studying old research will give a clear idea of the topic. To aid future researchers in this subject, we give a review of fragile watermarking approaches and some related papers presented in recent years. This paper presents a comparison of many relevant works in this field based on some of the outcomes and improvements gained in these studies, which focuses on the common characteristics that increase the effect of watermarking techniques such as invisibility, tamper detection, recovery, and security

Sine cosine bird swarm algorithm-based deep convolution neural network for reversible medical video watermarking

Sine cosine bird swarm algorithm-based deep convolution neural network for reversible medical video watermarking

Key-frame extraction based video watermarking using speeded up robust features and discrete cosine transform

Due to advancements in the internet and multimedia technologies, unauthorised users can easily modify video content. As a result, video authentication has been established as a viable solution for ensuring multimedia security. We propose a key-frame based video watermarking scheme based on discrete cosine transform (DCT). First, the pearson correlation coefficient (PCC) is used to detect the shot boundaries of the input video. To reduce the difficulties created by traditional video watermarking systems; an entropy measure is employed to detect key-frames from input video. Traditional schemes entail embedding the entire watermark into all frames of the video, which is inefficient and time-consuming. To improve the security, robustness, and imperceptibility of the proposed video watermarking scheme, speeded up robust feature points are extracted from each key-frame of the shot and used as reference points for embedding and detection of watermark. The embedded watermark is extracted blindly without using the original data during the extraction process. The results of the experiments reveal that the proposed technique effectively detects shot boundaries under a variety of camera operations and outperforms in terms of imperceptibility and resilience.