Spread spectrum-based video watermarking algorithms for copyright protection

Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen

Digital watermarking : applicability for developing trust in medical imaging workflows state of the art review

Medical images can be intentionally or unintentionally manipulated both within the secure medical system environment and outside, as images are viewed, extracted and transmitted. Many organisations have invested heavily in Picture Archiving and Communication Systems (PACS), which are intended to facilitate data security. However, it is common for images, and records, to be extracted from these for a wide range of accepted practices, such as external second opinion, transmission to another care provider, patient data request, etc. Therefore, confirming trust within medical imaging workflows has become essential. Digital watermarking has been recognised as a promising approach for ensuring the authenticity and integrity of medical images. Authenticity refers to the ability to identify the information origin and prove that the data relates to the right patient. Integrity means the capacity to ensure that the information has not been altered without authorisation. This paper presents a survey of medical images watermarking and offers an evident scene for concerned researchers by analysing the robustness and limitations of various existing approaches. This includes studying the security levels of medical images within PACS system, clarifying the requirements of medical images watermarking and defining the purposes of watermarking approaches when applied to medical images

Digital video watermarking techniques for secure multimedia creation and delivery.

Chan Pik-Wah.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 111-130).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.ivChapter 1 --- Introduction --- p.1Chapter 1.1 --- Background --- p.1Chapter 1.2 --- Research Objective --- p.3Chapter 1.3 --- Contributions --- p.4Chapter 1.4 --- The Structure of this Thesis --- p.6Chapter 2 --- Literature Review --- p.7Chapter 2.1 --- Security in Multimedia Communications --- p.8Chapter 2.2 --- Cryptography --- p.11Chapter 2.3 --- Digital Watermarking --- p.14Chapter 2.4 --- Essential Ingredients for Video Watermarking --- p.16Chapter 2.4.1 --- Fidelity --- p.16Chapter 2.4.2 --- Robustness --- p.17Chapter 2.4.3 --- Use of Keys --- p.19Chapter 2.4.4 --- Blind Detection --- p.20Chapter 2.4.5 --- Capacity and Speed --- p.20Chapter 2.4.6 --- Statistical Imperceptibility --- p.21Chapter 2.4.7 --- Low Error Probability --- p.21Chapter 2.4.8 --- Real-time Detector Complexity --- p.21Chapter 2.5 --- Review on Video Watermarking Techniques --- p.22Chapter 2.5.1 --- Video Watermarking --- p.25Chapter 2.5.2 --- Spatial Domain Watermarks --- p.26Chapter 2.5.3 --- Frequency Domain Watermarks --- p.30Chapter 2.5.4 --- Watermarks Based on MPEG Coding Struc- tures --- p.35Chapter 2.6 --- Comparison between Different Watermarking Schemes --- p.38Chapter 3 --- Novel Watermarking Schemes --- p.42Chapter 3.1 --- A Scene-based Video Watermarking Scheme --- p.42Chapter 3.1.1 --- Watermark Preprocess --- p.44Chapter 3.1.2 --- Video Preprocess --- p.46Chapter 3.1.3 --- Watermark Embedding --- p.48Chapter 3.1.4 --- Watermark Detection --- p.50Chapter 3.2 --- Theoretical Analysis --- p.52Chapter 3.2.1 --- Performance --- p.52Chapter 3.2.2 --- Capacity --- p.56Chapter 3.3 --- A Hybrid Watermarking Scheme --- p.60Chapter 3.3.1 --- Visual-audio Hybrid Watermarking --- p.61Chapter 3.3.2 --- Hybrid Approach with Different Water- marking Schemes --- p.69Chapter 3.4 --- A Genetic Algorithm-based Video Watermarking Scheme --- p.73Chapter 3.4.1 --- Watermarking Scheme --- p.75Chapter 3.4.2 --- Problem Modelling --- p.76Chapter 3.4.3 --- Chromosome Encoding --- p.79Chapter 3.4.4 --- Genetic Operators --- p.80Chapter 4 --- Experimental Results --- p.85Chapter 4.1 --- Test on Robustness --- p.85Chapter 4.1.1 --- Experiment with Frame Dropping --- p.87Chapter 4.1.2 --- Experiment with Frame Averaging and Sta- tistical Analysis --- p.89Chapter 4.1.3 --- Experiment with Lossy Compression --- p.90Chapter 4.1.4 --- Test of Robustness with StirMark 4.0 --- p.92Chapter 4.1.5 --- Overall Comparison --- p.98Chapter 4.2 --- Test on Fidelity --- p.100Chapter 4.2.1 --- Parameter(s) Setting --- p.101Chapter 4.2.2 --- Evaluate with PSNR --- p.101Chapter 4.2.3 --- Evaluate with MAD --- p.102Chapter 4.3 --- Other Features of the Scheme --- p.105Chapter 4.4 --- Conclusion --- p.106Chapter 5 --- Conclusion --- p.108Bibliography --- p.11

Robust and imperceptible digital video watermarking techniques.

Pengeluaran bahan video dan imej yang banyak dalam sistem berperantaraan komputer di Internet telah memberikan cabaran besar dalam bidang perlindungan hak milik. Banyak cetakan yang tidak sah telah dibuat dan usaha untuk membuktikan perlindungan hak milik terpelihara terhadap bahan media berkenaan adalah satu tugas yang mencabar. The massive production of image and video materials on the Computer Mediated Systems (CMS) over the Internet has created a challenge in the area of copyright protection. Numerous illegal copies have been made and efforts on proving the owner copyright of those media are indeed a challenging task

Image data hiding

Image data hiding represents a class of processes used to embed data into cover images. Robustness is one of the basic requirements for image data hiding. In the first part of this dissertation, 2D and 3D interleaving techniques associated with error-correction-code (ECC) are proposed to significantly improve the robustness of hidden data against burst errors. In most cases, the cover image cannot be inverted back to the original image after the hidden data are retrieved. In this dissertation, one novel reversible (lossless) data hiding technique is then introduced. This technique is based on the histogram modification, which can embed a large amount of data while keeping a very high visual quality for all images. The performance is hence better than most existing reversible data hiding algorithms. However, most of the existing lossless data hiding algorithms are fragile in the sense that the hidden data cannot be extracted correctly after compression or small alteration. In the last part of this dissertation, we then propose a novel robust lossless data hiding technique based on patchwork idea and spatial domain pixel modification. This technique does not generate annoying salt-pepper noise at all, which is unavoidable in the other existing robust lossless data hiding algorithm. This technique has been successfully applied to many commonly used images, thus demonstrating its generality

Watermarking scheme using slantlet transform and enhanced knight tour algorithm for medical images

Digital watermarking has been employed as an alternative solution to protect the medical healthcare system with a layer of protection applied directly on top of data stored. Medical image that is highly sensitive to the image processing and cannot tolerate any visual degradation has become the focus of digital watermarking. However, since watermarking introduces some changes on medical images, it is a challenge for medical image watermarking to maintain high imperceptibility and robustness at the same time. Research to date has tended to focus on the embedding method instead of the sequence of embedding of the watermarking itself. Also, although watermarking has been introduced into medical images as a layer of protection, it still cannot prevent a knowledgeable hacker from retrieving the watermark. Therefore, this research proposes a robust watermarking scheme with high imperceptibility for medical images to increase the effectiveness of the medical healthcare system in terms of perceptibility, embedding technique, embedding region and embedding sequence of the watermarking scheme. To increase imperceptibility of a watermark, this research introduces Dynamic Visibility Threshold, a new parameter that increases visual quality in terms of imperceptibility. It is a unique number which differs for each host image using descriptive statistics. In addition, two new concepts of embedding region, namely Embeddable zone (EBD) and Non-Embeddable zone (NEBD) to function as a non-parametric decision region to complicate the estimate of the detection function are also proposed. The sequence of embedding is shuffled using enhanced Knight Tour algorithm based on Slantlet Transform to increase the complexity of the watermarking scheme. A significant result from the Peak Signal-to-Noise Ratio (PSNR) evaluation showing approximately 270 dB was obtained, suggesting that this proposed medical image watermarking technique outperforms other contemporary techniques in the same working domain. Based on the experimental result using the standard dataset, all host images are resilient to Salt and Pepper Noise, Speckle Noise, Poisson Noise, Rotation and Sharpen Filter with minimum Bit Error Rate (BER) of 0.0426 and Normalized Cross-Correlation (NCC) value of as high as 1. Since quartile theory is used, this experiment has shown that among all three quartiles, the Third Quartile performs the best in functioning as Dynamic Visibility Threshold (DVT) with 0 for BER and 1 for NCC evaluation

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography

Data hiding is the process of embedding information into a noise-tolerant signal such as a piece of audio, video, or image. Digital watermarking is a form of data hiding where identifying data is robustly embedded so that it can resist tampering and be used to identify the original owners of the media. Steganography, another form of data hiding, embeds data for the purpose of secure and secret communication. This survey summarises recent developments in deep learning techniques for data hiding for the purposes of watermarking and steganography, categorising them based on model architectures and noise injection methods. The objective functions, evaluation metrics, and datasets used for training these data hiding models are comprehensively summarised. Finally, we propose and discuss possible future directions for research into deep data hiding techniques

Scale Invariant and Rotation Invariant Image Watermarking

The scheme proposed is an improved version of the image watermarking scheme in "Scale-Invariant Image Watermarking via Optimization Algorithm for Quantizing Randomized Statistics". The previous watermarking scheme was scale invariant but not rotation invariant. In this thesis we propose to modify the method by incorporating Zernike moment transformation to make it rotationally invariant, thus making it robust against synchronization attacks.Computer Science Departmen