Video Watermarking Technique Research Articles

A Video Dual-Domain Blind Watermarking Algorithm Based on Hadamard Transform

Addressing the compatibility challenges surrounding the robustness and reversibility of existing video watermarking techniques, this study introduces a novel video dual-domain blind watermarking algorithm leveraging the Hadamard transform. Specifically tailored for H.264 video copyright protection, the algorithm initially organizes video frames and identifies key frames for watermark embedding. Prior to embedding, the robust watermark undergoes coding preprocessing to optimize its integration. Subsequently, a 4×4 block is expanded based on the selected embedding position within the frame, followed by the application of the Hadamard transform to the enlarged block. The 1-bit robust watermark information is then embedded via the coefficient pair located in the first row of the Hadamard coefficient matrix corresponding to the expanded block. Additionally, a reversible watermark, designed to mitigate the distortions introduced during robust embedding, is generated and embedded into the remaining coefficients of the coefficient matrix using reversible embedding techniques. During watermark extraction, the dual-domain watermark can be retrieved exclusively through reversible extraction methodologies by analyzing the size relationship of coefficient pairs, eliminating the need for access to the original video data. To bolster the algorithm’s robustness, a majority-subordinate voting system is devised and implemented, effectively enhancing its resilience. Experimental findings demonstrate that, compared to similar approaches, this algorithm not only enhances the reversibility of video restoration but also exhibits superior robustness and meets the requirements for imperceptibility.

Machine learning based weight optimized genetic algorithm for digital video watermarking technique

Machine learning based weight optimized genetic algorithm for digital video watermarking technique

Deep Learning-Based Watermarking Techniques Challenges: A Review of Current and Future Trends

The digital revolution places great emphasis on digital media watermarking due to the increased vulnerability of multimedia content to unauthorized alterations. Recently, in the digital boom in the technology of hiding data, research has been tending to perform watermarking with numerous architectures of deep learning, which has explored a variety of problems since its inception. Several watermarking approaches based on deep learning have been proposed, and they have proven their efficiency compared to traditional methods. This paper summarizes recent developments in conventional and deep learning image and video watermarking techniques. It shows that although there are many conventional techniques focused on video watermarking, there are yet to be any deep learning models focusing on this area; however, for image watermarking, different deep learning-based techniques where efficiency in invisibility and robustness depends on the used network architecture are observed. This study has been concluded by discussing possible research directions in deep learning-based video watermarking.

Video watermarking technique using motion vectors to video authentication

Video watermarking technique using motion vectors to video authentication

Optimal Information Hiding: Advanced Bitstream‐Based Watermarking for Secure and Efficient Integration of Image Data in Digital Videos

Video watermarking is a technique used to embed a visible or invisible mark onto a video file in order to claim ownership, protect intellectual property rights, and detect unauthorized users. The issue of video piracy arises due to the advancement of Internet services and the utilization of various storage technologies. This problem becomes particularly significant with the widespread propagation of media through online channels. The constant progress in sharing of data, videos, images, and applications necessitates the implementation of measures focused on security and the protection of intellectual ownership rights. To address this issue, we proposed a novel Bitstream video watermarking technique that integrates cutting‐edge methodologies to seamlessly embed image data within digital videos. This technique stands apart from less sophisticated watermarking methods by capitalizing on spatial and temporal domain concepts in video processing. An experiment is conducted to analyze the time required for the insertion and extraction processes to gain insights into the performance of bitstream watermarking in the video. While enhancing the existing approach, we systematically explored diverse strategies aimed at augmenting watermark capacity, bolstering robustness, and heightening visual imperceptibility. These strategies encompassed the intricate infusion of watermark fragments into the frame area through chaotic mechanisms, the integration of error‐correcting codes to ensure data fidelity, and the selective omission of dynamic video segments during information extraction processes. Rigorous experimentations are undertaken by the constraints of lossy compression scenarios, maintaining equivalent or reduced bitrate parameters. The findings substantiate the favorable outcomes stemming from the implemented enhancement, affirming the tangible suitability of the phase watermarking technique for the protection of video copyrights. In order to assess the quality of the bitstream video watermarking technique, the peak signal‐to‐noise ratio (PSNR), structural similarity index (SSIM), and normalized correlation coefficient (NCC) are computed and examined by the testing data. The suggested model achieved a PSNR value up to 32.52 dB, SSIM value up to 0.97, and NCC value is 1. The dynamic range (DR) and spatial resolution (SR) are measured in the evaluation process. Security is enhanced significantly after implementing the multifaceted approach. The watermarking scheme is more robust and can effectively resist the potential attacks. In summary, this study advances the field of video watermarking by proposing a sophisticated bitstream technique and rigorously evaluating its performance. The outcomes underscore its practical viability for copyright protection, contributing to a more secure digital media landscape.

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 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

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.

Video Watermarking System

Abstract: Advanced video watermarking may be a procedure for inserting extra information beside video flag. Inserted information is utilized for copyright proprietor recognizable proof. A number of video watermarking techniques are proposed. These methods misuse distinctive ways in arrange to implant a strong watermark and to preserve the first video flag constancy. In this paper, Computerized video watermarking strategies and assaults on watermarks are displayed.

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 Robust Video Watermarking Scheme with Squirrel Search Algorithm

Advancement in multimedia technology has resulted in protection against distortion, modification, and piracy. For implementing such protection, we have an existing technique called watermarking but obtaining desired distortion level with sufficient robustness is a challenging task for watermarking in multimedia applications. In the paper, we proposed a smart technique for video watermarking associating meta-heuristic algorithms along with an embedding method to gain an optimized efficiency. The main aim of the optimization algorithm is to obtain solutions with maximum robustness, and which should not exceed the set threshold of quality. To represent the accuracy of the proposed scheme, we employ a popular video watermarking technique (DCT domain) having frame selection and embedding method for watermarking. A squirrel search algorithm is chosen as a meta-heuristic algorithm that utilizes the stated fitness function. The results indicate that quality constraint is fulfilled, and the proposed technique gives improved robustness against different attacks with several quality thresholds. The proposed technique could be practically implemented in several multimedia applications such as the films industry, medical imagery, OOT platforms, etc.

Development of payload capacity enhanced robust video watermarking scheme based on symmetry of circle using lifting wavelet transform and SURF

Using simple image and video editing software it is relatively easy to pirate the digital contents at the cost of huge revenue loss to the content owner. Entertainment is the key industry that is overwhelmed by huge financial loss due to digital piracy. WhatsApp, Facebook, Instagram, Pinterest and Twitter are some of the massive social media platforms that are used by millions of users. Many of the users share digital content without giving credit to the owner. Digital watermarking is an efficient technique to protect the digital rights and legal compensation of content owners. Due to the poor selection of watermarking locations, most of the state-of-art methods were fall short to preserve the relationships among the host data. Hence such methods were not efficient to provide safeguards against digital piracy. Therefore, this paper proposes a digital video watermarking technique that analyzes, extracts and processes the useful patterns or features of data based on the symmetry of the circle using 2D-Lifting Wavelet Transform (2D-LWT) and Speeded-Up Robust Features (SURF). SURF method is used to obtain five invariant feature points on an approximation part of 2D-LWT utilizing the luminance component of each video frame. The invariant points serve as centers of the circles used to find the embed locations. The maximum intensity value point in all the points on the circumference of the 1/8 part of the circle is then calculated to serve as an embedding location. Three other points in different quadrants are simply obtained using the concept of symmetry of the circle. After applying temporal desynchronization, compression and insertion of noise attacks the video is assessed through subjective and objective evaluation metrics. The results reveal a high degree of correlation (close to one) and good visual transparency which proves that the proposed scheme is superior for practical applications.

A Novel Optimized Graph-Based Transform Watermarking Technique to Address Security Issues in Real-Time Application

The multimedia technologies are gaining a lot of popularity these days. Many unauthorized persons are gaining the access of multimedia such as videos, audios, and images. The transmission of multimedia across the Internet by unauthorized person has led to the problem of illegal distribution. The problem arises when copyrighted data is getting accessed without the knowledge of copyright owner. The videos are the most attacked data during COVID-19 pandemic. In this paper, the frame selection video watermarking technique is proposed to tackle the issue. The proposed work enlightens frame selection followed by watermarking embedding and testing of the technique against various attacks. The embedding of the watermark is done on selected frames of the video. The additional security feature Hyperchaotic Encryption is applied on watermark before embedding. Watermark embedding is done using graph-based transform and singular-valued decomposition and the performance of the technique is further optimized using hybrid combination of grey wolf optimization and genetic algorithm. Many researchers face the challenge of quality loss after embedding of watermark. Proposed technique will aim to overcome those challenges. A total of 6 videos (Akiyo, Coastguard, Foreman, News, Bowing, and Pure Storage) are used for carrying out research work. The performance evaluation of the proposed technique has been carried out after processing it against practical video processing attacks Gaussian noise, sharpening, rotation, blurring, and JPEG compression.

Survey of Recent Video Watermarking Techniques

With the development of the Internet coupled with expanding the accessibility of multimedia, various copyright issues have resulted. Several researchers have been working on watermarks to provide the security, durability, and a perception of multimedia. This paper a review of some recent works is presented related to video watermarking techniques, this study focuses on the pros and cons of recent video watermarking, areas of application, and the different types and attacks that are standing against these watermarking techniques. The results obtained from this study showed that watermark techniques based on the transfer domain, are more popular than those of the spatial domain.

A Secured Frame Selection Based Video Watermarking Technique to Address Quality Loss of Data: Combining Graph Based Transform, Singular Valued Decomposition, and Hyperchaotic Encryption

The advancement of Internet technologies has led to the availability of audios, images, and videos in different forms. The unauthorized users are exploiting the use of multimedia by transmitting them on various Internet sites to earn money unethically without the intervention of the original copyright holder. Watermarking is a technique used to hide the signal known as watermark inside multimedia data that is not visible to the intruder to manipulate any information. In this paper, a secured watermarking approach is developed to tackle issues related to copyright protection and ownership identification. A Secured Graph Based Transform, Singular Valued Decomposition, and Hyperchaotic Encryption hybrid techniques are proposed. The watermark cannot be embedded in every frame of the video as it adds to the size of the video and watermark can be easily retrieved by an intruder. Therefore, the frame selection algorithm has been proposed in the given work. Adding watermark in the frame adds to the challenge of quality loss. The quality loss is addressed in this work. Various attacks have been applied on the watermarked frames to calculate the performance of the proposed technique using quality metrics: Peak Signal to Noise Ratio, Structural Similarity Index, Normalized Correlation, and Bit Error Rate. The results indicate that the proposed technique is effective against various attack scenarios.

Development and Implementation of a Video Watermarking Method Based on DCT Transform

This paper presents a new color video watermarking technique based on the one-dimensional Discrete Cosine Transform (DCT). This approach uses a differential embedding technique to insert the bits of the watermark into the video frames so that the extraction process is blind and straightforward. To further ensure the security of the method, the binary image watermark is scrambled using Arnold transform before embedded into the video segment. Also, a color space transformation from Red, Green and Blue (RGB) to YUV is performed in order to deal with the color nature of the video segments. The proposed approach exhibits good robustness against a wide range of attacks such as video compression, cropping, Gaussian filtering, and noise adding. Finally, we propose an implementation of the video watermarking technique using the Raspberry Pi 3 platform. Nearly the same remarks may be made as in the simulation resultsconcerning the robustness against video compression attacks

Security of Finger Prints with Video Watermarking Techniques Based On DWT and SVD

Content producers and service providers face highly important challenges in securing digital video content. As watermarking is an important copyright protection technology, this literature includes several methods of combining data into a multimedia component. Due to its increasing application, in recent watermark schemes, the Discrete Wavelet Transformation (DWT) is used. In this text we suggest a DWT and the SVDbased hybrid system. After the image is separated into four strips, we add SVD to each strip and adjust the specific values into the same detail. Modification at all frequencies allows a framework to be established that is consistent with a broad range of threats.

WITHDRAWN: A review on video watermarking techniques for compressed domain with optimization algorithms

Abstract The unauthorized usage of electronic data has resulted in challenges that are many like copyright protection as well as ownership identification. With the rapid advancement of electronic media, there’s an important need for authentication (similar to what we come across in a currency note) in such a manner that authorization and originality may be demonstrated. Video watermarking is a technique utilized to stop the illegal manipulation & distribution of digital videos by embedding a watermark on selected frames so that it’s irremovable and imperceptible. This paper presents an evaluation of video watermarking techniques; along with analysis has been done on frame selection mechanism followed optimization algorithms to improve embedding processes.

SVD Based Robust Unsighted Video Watermarking Technique for different attacks

Nowadays, digital watermark protects intellectual property in the digital world. In this article, a new singular value decomposition (SVD) based robust unsighted video watermarking technique is used for protection of copyright or owns individual work. The Singular Value Decomposition is used in this method to embed the information in a video file. In the embedded process the information generally referred to as watermark, which is of the form either audio, text, video, or any binary image or digital image. The embedded information can be identified in this process without considering the mechanisms of the original video, or any other knowledge about the encoded video ‘s main singular values. Singular value decomposition is used in embedding the information as well as retrieving the information from the embedded watermarked video. SVD based robust unsighted video technique shows that it bears required robustness on various attacks like MPEG-2 compressed video, median filtered, small rescaled, and rotational videos. In the experimental result, it is noticed that the unsighted video watermarking technique has visible quality and robustness for various attacks. In which watermark is installed in uniquely chose particular estimations of the video, and the first request can be kept up to recovering the data in our method and it has been indicated roust to different attacks.