Digital watermarking techniques have been developed to protect the copyright of media signals. This study aims to provide a universal review and background about the watermarking definition, concept and the main contributions in this field. The study will start with a general view of digital data, the Internet and the products of these two, namely, the multimedia and the e-commerce. The study will presents an extensive and deep literature review of the field of digital watermarking and watermarking algorithms.
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Digital watermarking techniques have been developed to protect the copyright of media signals. Different watermarking schemes have been suggested for multimedia content (images, video and audio signal). This study aims to provide an extensive literature review of the multimedia copyright protection. It presents a universal review and background about the watermarking definition, concept and the main contributions in this field.
Digital Intellectual Property
Information is becoming widely available via global networks. These connected networks allow cross-references between databases. The advent of multimedia is allowing different applications to mix sound, images, and video and to interact with large amounts of information (e.g., in e-business, distance education, and human-machine interface). The industry is investing to deliver audio, image and video data in electronic form to customers, and broadcast television companies, major corporations and photo archives are converting their content from analogue to digital form. This movement from traditional content, such as paper documents, analogue recordings, to digital media is due to several advantages of digital media over the traditional media. Some of these advantages are:
The quality of digital signals is higher than that of their corresponding analogue signals. Traditional assets degrade in quality as time passes. Analogue data require expensive systems to obtain high quality copies, whereas digital data can be easily copied without loss of fidelity.
Digital data (audio, image and video signals) can be easily transmitted over networks, for example the Internet. A large amount of multimedia data is now available to users all over the world. This expansion will continue at an even greater rate with the widening availability of advanced multimedia services like electronic commerce, advertising, interactive TV, digital libraries, and a lot more.
Exact copies of digital data can be easily made. This is very useful but it also creates problems for the owner of valuable digital data like precious digital images. Replicas of a given piece of digital data cannot be distinguished and their origin cannot be confirmed. It is impossible to determine which piece is the original and which is the copy.
It is possible to hide some information within digital data in such a way that data modifications are undetectable for the human senses.
Copyright Protection of Intellectual Property
An important factor that slows down the growth of multimedia-networked services is that authors, publishers and providers of multimedia data are reluctant to allow the distribution of their documents in a networked environment. This is because the ease of reproducing digital data in their exact original form is likely to encourage copyright violation, data misappropriation and abuse. These are the problems of theft and distribution of intellectual property. Therefore, creators and distributors of digital data are actively seeking reliable solutions to the problems associated with copyright protection of multimedia data.
Moreover, the future development of networked multimedia systems, in particular on open networks like the Internet, is conditioned by the development of efficient methods to protect data owners against unauthorized copying and redistribution of the material put on the network. This will guarantee that their rights are protected and their assets properly managed. Copyright protection of multimedia data has been accomplished by means of cryptography algorithms to provide control over data access and to make data unreadable to non-authorized users. However, encryption systems do not completely solve the problem, because once encryption is removed there is no more control on the dissemination of data. The concept of digital watermarking arose while trying to solve problems related to the copyright of intellectual property in digital media. It is used as a means to identify the owner or distributor of digital data. Watermarking is the process of encoding hidden copyright information since it is possible today to hide information messages within digital audio, video, images and texts, by taking into account the limitations of the human audio and visual systems.
Digital Watermarking: What, Why, When and How?
It seems that digital watermarking is a good way to protect intellectual property from illegal copying. It provides a means of embedding a message in a piece of digital data without destroying its value. Digital watermarking embeds a known message in a piece of digital data as a means of identifying the rightful owner of the data. These techniques can be used on many types of digital data including still imagery, movies, and music.
What is Digital Watermarking?
A digital watermark is a signal permanently embedded into digital data (audio, images, video, and text) that can be detected or extracted later by means of computing operations in order to make assertions about the data. The watermark is hidden in the host data in such a way that it is inseparable from the data and so that it is resistant to many operations not degrading the host document. Thus by means of watermarking, the work is still accessible but permanently marked.
Digital watermarking techniques derive from steganography, which means covered writing (from the Greek words stegano or “covered” and graphos or “to write”). Steganography is the science of communicating information while hiding the existence of the communication. The goal of steganography is to hide an information message inside harmless messages in such a way that it is not possible even to detect that there is a secret message present. Both steganography and watermarking belong to a category of information hiding, but the objectives and conditions for the two techniques are just the opposite. In watermarking, for example, the important information is the “external” data (e.g., images, voices, etc.). The “internal” data (e.g., watermark) are additional data for protecting the external data and to prove ownership. In steganography, however, the external data (referred to as a vessel, container, or dummy data) are not very important. They are just a carrier of the important information. The internal data are the most important. On the other hand, watermarking is not like encryption. Watermarking does not restrict access to the data while encryption has the aim of making messages unintelligible to any unauthorized persons who might intercept them. Once encrypted data is decrypted, the media is no longer protected. A watermark is designed to permanently reside in the host data. If the ownership of a digital work is in question, the information can be extracted to completely characterize the owner.
Digital watermarking is an enabling technology for e-commerce strategies: conditional and user-specific access to services and resources. Digital watermarking offers several advantages. The details of a good digital watermarking algorithm can be made public knowledge. Digital watermarking provides the owner of a piece of digital data the means to mark the data invisibly. The mark could be used to serialize a piece of data as it is sold or used as a method to mark a valuable image. For example, this marking allows an owner to safely post an image for viewing but legally provides an embedded copyright to prohibit others from posting the same image. Watermarks and attacks on watermarks are two sides of the same coin. The goal of both is to preserve the value of the digital data. However, the goal of a watermark is to be robust enough to resist attack but not at the expense of altering the value of the data being protected. On the other hand, the goal of the attack is to remove the watermark without destroying the value of the protected data. The contents of the image can be marked without visible loss of value or dependence on specific formats. For example a bitmap (BMP) image can be compressed to a JPEG image. The result is an image that requires less storage space but cannot be distinguished from the original. Generally, a JPEG compression level of 70% can be applied without humanly visible degradation. This property of digital images allows insertion of additional data in the image without altering the value of the image. The message is hidden in unused “visual space” in the image and stays below the human visible threshold for the image.
When Did the Technique Originate?
The idea of hiding data in another media is very old, as described in the case of steganography. Nevertheless, the term digital watermarking first appeared in 1993, when Tirkel et al. (1993) presented two techniques to hide data in images. These methods were based on modifications to the least significant bit (LSB) of the pixel values.
How Can We Build an Effective Watermarking Algorithm?
It is desired that watermarks survive image-processing manipulations such as rotation, scaling, image compression and image enhancement, for example. Taking advantage of the discrete wavelet transform properties and robust features extraction techniques are the new trends that are used in the recent digital image watermarking methods. Robustness against geometrical transformation is essential since image-publishing applications often apply some kind of geometrical transformations to the image, and thus, an intellectual property ownership protection system should not be affected by these changes.
Visible vs. Invisible Watermarks
Digital watermarking is divided into two main categories: visible and invisible. The idea behind the visible watermark is very simple. It is equivalent to stamping a watermark on paper, and for this reason its sometimes said to be digitally stamped. An example of visible watermarking is provided by television channels, like BBC, whose logo is visibly superimposed on the corner of the TV picture. Invisible watermarking, on the other hand, is a far more complex concept. It is most often used to identify copyright data, like author, distributor, and so forth.
Though a lot of research has been done in the area of invisible watermarks, much less has been done for visible watermarks. Visible and invisible watermarks both serve to deter theft but they do so in very different ways. Visible watermarks are especially useful for conveying an immediate claim of ownership (Mintzer, Braudaway & Yeung, 1997). Their main advantage, in principle at least, is the virtual elimination of the commercial value of a document to a would-be thief, without lessening the document’s utility for legitimate, authorized purposes. Invisible watermarks, on the other hand, are more of an aid in catching a thief than for discouraging theft in the first place (Mintzer et al., 1997; Swanson et al., 1998).
There are different classifications of invisible watermarking algorithms. The reason behind this is the enormous diversity of watermarking schemes. Watermarking approaches can be distinguished in terms of watermarking host signal (still images, video signal, audio signal, integrated circuit design), and the availability of original signal during extraction (non-blind, semi-blind, blind). Also, they can be categorized based on the domain used for watermarking embedding process, as shown in Figure 1. The watermarking application is considered one of the criteria for watermarking classification. Figure 2 shows the subcategories based on watermarking applications.
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Digital Watermarking Algorithms
Current watermarking techniques described in the literature can be grouped into three main classes. The first includes the transform domain methods, which embed the data by modulating the transform domain signal coefficients. The second class includes the spatial domain techniques. These embed the watermark by directly modifying the pixel values of the original image. The transform domain techniques have been found to have the greater robustness, when the watermarked signals are tested after having been subjected to common signal distortions. The third class is the feature domain technique. This technique takes into account region, boundary and object characteristics. Such watermarking methods may present additional advantages in terms of detection and recovery from geometric attacks, compared to previous approaches.
The algorithms in this study are organized according to their embedding domain, as indicated in Figure 1. These are grouped into:
- Spatial domain techniques
- Transform domain techniques
- Feature domain techniques
However, due to the amount of published work in the field of watermarking technology, the main focus will be on wavelet-based watermarking technique papers. The wavelet domain is the most efficient domain for watermarking embedding so far. However, the review considers some other techniques, which serve the purpose of giving a broader picture of the existing watermarking algorithms. Some examples of spatial domain and fractal-based techniques will be reviewed.
Spatial Domain Techniques
This section gives a brief introduction to the spatial domain technique to gives some background information about watermarking in this domain. Many spatial techniques are based on adding fixed amplitude pseudo noise (PN) sequences to an image. PN sequences are used as the “spreading key” when considering the host media as the noise in a spread spectrum system, where the watermark is the transmitted message. In this case, the PN sequence is used to spread the data bits over the spectrum to hide the data.
Transform Domain Techniques
Many transform-based watermarking techniques have been proposed. To embed a watermark, a transformation is first applied to the host data, and then modifications are made to the transform coefficients. In this section, the state of the art of the current watermarking algorithms using the transform domain is presented. The section has three main parts, including discussions of waveletbased watermarking, DCT-based watermarking and fractal domain watermarking.
Digital Watermarking Using Wavelet Decomposition
This algorithm can easily be built into video watermarking applications based on a 3-D wavelet transform due to its simple structure. The hierarchical nature of the wavelet representation allows multi-resolutional detection of the digital watermark, which is a Gaussian distributed random vector added to all the high pass bands in the wavelet domain.
Discrete Cosine Transform-Based Digital Watermarking
Several watermarking algorithms have been proposed to utilize the DCT. However, the Cox et al. (1995, 1997) and the Koch and Zhao (1995) algorithms are the most well-known DCT-based algorithms. Cox et al. (1995) proposed the most well-known spread spectrum watermarking schemes. Figure 3 shows the block diagram of the Cox algorithm. The image is first subjected to a global DCT. Then, the 1,000 largest coefficients in the DCT domain are selected for watermarking. They used a Gaussian sequence of pseudo-random real numbers of length 1,000 as a watermark. This approach achieves good robustness against compression and other common signal processing attacks. This is a result of the selection of perceptually significant transform domain coefficients. However, the algorithm is in a weak position against the invariability attack proposed by Craver (1997). Also, the global DCT employed on the image is computationally expensive.
Fractal Transform-Based Digital Watermarking
Though a lot of work has been done in the area of invisible watermarks using the DCT and the wavelet-based methods, relatively few references exist for invisible watermarks based on the fractal transform. The reason for this might be the computational expense of the fractal transform. In fractal analysis, similar patterns are identified in an image and only a limited amount of binary code can be embedded using this method. Since fractal analysis is computationally expensive and some images do not have many large self-similar patterns, the techniques may not be suitable for general use.
Feature Domain Techniques (Second Generation Watermarking)
First generation watermarking (1GW) methods have been mainly focused on applying the watermarking on the entire image/video domain. However, this approach is not compatible with novel approaches for still image and video compression. JPEG2000 and MPEG4/7 standards are the new techniques for image and video compression. They are region or object-based, as can be seen in the compression process. Also, the 1GW algorithms proposed so far do not satisfy the watermarking requirements.
Second generation watermarking (2GW) was developed in order to increase the robustness and invisibility and to overcome the weaknesses of 1GW. The 2GW methods take into account region, boundary and object characteristics and give additional advantages in terms of detection and recovery from geometric attacks compared to first generation methods. Exploiting salient region or object features and characteristics of the image achieve this. Also, 2GW methods may be designed so that selective robustness to different classes of attacks is obtained. As a result, watermark flexibility will be improved considerably.
Digital Watermarking and Image Processing Attacks
Digital watermarking was claimed to be the ultimate solution for copyright protection over the Internet when the concept of digital watermarking was first presented. However, some problems related to robustness and security of watermarking algorithms to intentional or unintentional attacks still remain unsolved. These problems must be solved before digital watermarking can be claimed to be the ultimate solution for copyright ownership protection in digital media. One of these problems is the effect of geometrical transformations such as rotation, translation and scaling on the recovery of the watermark. Another is the security of the watermarking algorithm when intentional attackers make use of knowledge of the watermarking algorithm to destroy or remove the watermark.
Watermarking Standardization Issue
The most important question about watermarking technology is whether watermarking will be standardized and used in the near future. There are several movements to standardize watermarking technology, but no one standard has prevailed at this moment in time. Some researchers have been working to develop a standardized framework for protecting digital images and other multimedia content through technology built into media files and corresponding application software. However, they have lacked a clear vision of what the framework should be or how it would be used.
In addition, there was a discussion about how and whether watermarking should form part of the standard during the standardization process of JPEG2000. The requirements regarding security have been identified in the framework of JPEG2000. However, there has been neither in-depth clarification nor a harmonized effort to address watermarking issues. It is important to deduce what really needs to be standardized for including the watermarking concept in JPEG2000 and to what extent. The initial drafts of the JPEG2000 standard did not mention the issue of watermarking. However, there is a plan to examine how watermarking might be best applied within JPEG2000. The features of a given watermarking scheme are likely to offer designers an opportunity to integrate watermarking technology into JPEG2000 for different application such as distributing images on the Internet. Also, standardization of digital watermarking will influence the progress in imaging standards of JPEG2000 where the data security will be part of this standard. Therefore, the likelihood is that watermarking technology will be used in conjunction with JPEG2000 (Clark, 2000).
Nevertheless, the future seems bright for digital watermarking. Many companies have already been active in digital watermarking research. For example, Microsoft has developed a prototype system that limits unauthorized playback of music by embedding a watermark that remains permanently attached to audio files. Such technology could be included as a default playback mechanism in future versions of the Windows operating system. If the music industry begins to include watermarks in its song files, Windows would refuse to play copyrighted music released after a certain date that was obtained illegally. Also, Microsoft Research has also invented a separate watermarking system that relies on graph theory to hide watermarks in software. Normally the security technology is hack able. However, if the technology is combined with proper legal enforcement, industry standards and respects of the privacy of individuals seeking to legitimately use intellectual property, digital watermarking will encourage content creators to trust the Internet more. There is a tremendous amount of money at stake for many firms. The value of illegal copies of multimedia content distributed over the Internet could reach billions of dollars a year. It will be interesting to see how the development and adoption of digital watermarking plays out. With such high stakes involved for entertainment and other multimedia companies, they are likely to keep pushing for (and be willing to pay for) a secure technology that they can use to track and reduce copyright violation and capture some of their foregone revenues. Finally, it is expected that a great deal of effort must still be put into research before digital image watermarking can be widely accepted as legal evidence of ownership.
This study was started with a general view of digital data, the Internet and the products of these two, namely, multimedia and e-commerce. It provided some initial background and history of digital watermarking. This study gave an extensive and deep literature review of the field of digital watermarking. The concept of digital watermarking and the requirements of digital watermarking were discussed and digital watermarking algorithms were reviewed. They were grouped into three main collections based on the embedding domain, that is, spatial domain techniques, transform domain techniques or feature domain techniques. The algorithm of the frequency domain were further subdivided into wavelet, DCT and fractal transform techniques. Finally, the future perspective of digital watermarking was highlighted.
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