Digital Image Watermarking
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07-10-2010, 10:43 AM

.doc   Digital Image Watermarking.doc (Size: 210.5 KB / Downloads: 311)

Digital Image Watermarking


The development of effective digital image copyright protection methods have recently become an urgent and necessary requirement in the multimedia industry due to the ever-increasing unauthorized manipulation and reproduction of original digital objects. The new technology of digital watermarking has been advocated by many specialists as the best method to such multimedia copyright protection problem. Its expected that digital watermarking will have a wide-span of practical applications such as digital cameras, medical imaging, image databases, and video-on-demand systems, among many others.In order for a digital watermarking method to be effective it should be imperceptible, and robust to common image manipulations like compression, filtering, rotation, scaling cropping, collusion attacks among many other digital signal processing operations. Current digital image watermarking techniques can be grouped into two major classes: spatial-domain and frequency-domain watermarking techniques. Compared to spatial domain techniques, frequency-domain watermarking techniques proved to be more effective with respect to achieving the imperceptibility and robustness requirements of digital watermarking algorithms. Commonly used frequency-domain transforms include the Discrete Wavelet Transform (DWT), the Discrete Cosine Transform (DCT) and Discrete Fourier Transform (DFT). However, DWT has been used in digital image watermarking more frequently due to its excellent spatial localization and multi-resolution characteristics,which are similar to the theoretical models of the human visual system. Further performance improvements in DWT-based digital image watermarking algorithms could be obtained by combining DWT with DCT. The idea of applying two transform is based on the fact that combined transforms could compensate for the drawbacks of each other, resulting in effective watermarking.In this paper, we will describe a digital image watermarking algorithm based on combining two transforms; DWT and DCT. Watermarking is done by altering the wavelets coefficients of carefully selected DWT sub-bands, followed by the application of the DCT transform on the selected sub-bands.
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16-03-2011, 02:27 PM

.ppt   PPT FOR DIGITAL IMAGE WATERMARKING.ppt (Size: 815.5 KB / Downloads: 267)

we start by first characterizing the most important and distinguishing features of wavelet-based watermarking schemes. Application scenario,copyright protection is considered and building on the experience that was gained, implemented two distinguishing watermarking schemes. Detailed comparison and obtained results are presented and discussed.
Water marking

 Types of Watermarked Images:
1.Visible watermarking
2.Invisible watermarking
 Discrete Wavelet Transform
 The discrete wavelet transform (DWT) has gained widespread acceptance in signal processing and image compression.
 Recently the TIF committee has released its new image coding standard, TIF-2000, which has been based upon DWT.
 Discrete Wavelet Transform
 2-D DWT for Image
 Discrete Wavelet Transform
 Discrete Wavelet Transform
 2-D DWT for Image
 Discrete Wavelet Transform
 Advantages of DWT
 Allows good localization both in time and spatial frequency domain.
 Better identification of which data is relevant to human perceptionà higher compression ratio
 Higher flexibility: Wavelet function can be freely chosen
Discrete Wavelet Transform
Image Comparison
Disadvantages of DWT

 The cost of computing DWT as compared to DCT is higher.
 Longer compression time
Future scope
 The work presented in this project and implimentation is not user friendly i.e. one can provide a graphical user interface for the work that has been presented. Also the effective retrieving of the image when passed through a lossy channel can be considered for further work. The compression of the watermarked image can also be considered in this process
 Watermarking has been used as a tool for embedding image for copyright protection. It is also used for transmission of the data securely and also provided assistance to management of information.
 Broadcast Monitoring (Television news often contains watermarked video from international agencies)
 Copyright protection
 Fingerprinting (Different recipients get differently watermarked content)
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17-05-2012, 01:51 PM

Digital Image Watermarking

.pdf   digital watermarking.pdf (Size: 2.19 MB / Downloads: 211)


Watermarking is a technique used to hide data or identifying information within digital
multimedia. Our discussion will focus primarily on the watermarking of digital images, though
digital video, audio, and documents are also routinely watermarked. Digital watermarking is
becoming popular, especially for adding undetectable identifying marks, such as author or
copyright information. Because of this use, watermarking techniques are often evaluated based
on their invisibility, recoverability, and robustness. Our goal was to implement two different
watermarking methods and evaluate their susceptibility to attack by various image processing
techniques. Additionally, we wanted to create a GUI that would allow users unfamiliar with
Matlab to add and extract watermarks, as well as evaluate their respective robustness based on a
few morphological image attacks.
After learning about watermarking by bit-plane slicing in class, we were very interested
to investigate the process by which one watermarks an image, as well as the degree to which the
original image is changed by the watermarking process. To help us learn how images can be
watermarked, we decided to implement two watermarking techniques, watermarking by bit-plane
slicing and watermarking using the Cox method. It was extremely difficult to decide which
watermarking methods to implement, because there are a multitude of different methods by
which to watermark an image. The Cox method and the bit-plane method allowed us to take two
very different approaches to watermarking. We got to work in both the special and frequency
domain, as well as having different goals for each method. Our bit-plane slicing approach is
designed to work primarily as a fragile watermark. A fragile watermark shows the degree to
which changes are made to an image. The Cox method, on the other hand, is designed to be
robust. It works in the frequency domain, allowing it to resist many common attacks to the
In implementing these methods, we had to learn and create the processes to add a
watermark and extract a watermark from digital images. To evaluate the degree to which
watermarking affects the original image, the GUI was designed to display image difference
graphically as well as numerically in a relative error format. This helps the user evaluate the
invisibility of the watermark, as they can compare the changes watermarking makes to the
original image. When the user extracts a watermark from an image, the difference between the
watermarks is also shown both graphically and numerically. This will help the user decide if a
watermark can be consistently recovered with the given method.


In applying watermarks, our focus was on invisibility, recoverability, and robustness. All
of these are intricately linked. The less the image is affected, the easier it is to remove the
watermark; recoverability is heavily reliant on robustness, for the watermark must still be present
even after morphological attacks. Attacks may be accidental or intentional, but all images that
are digitally watermarked may be subject to attack. Most attacks are attempts to alter the image
in order to destroy the watermark while preserving the image. Since watermarks may be hidden
copyrights, this is extremely undesirable.
In order to address the issue of robustness, we decided to allow the user to use seven
different morphological attacks to see how the extracted watermark is affected. The
morphological attacks that are provided in the GUI are image scaling and cropping, as well as
Gaussian low-pass (blur) filtering, unsharp contrast-enhancement filtering, averaging filtering,
and circular averaging filtering. These attacks can be used to alter a watermarked image. The
watermark can then be extracted and compared to the original watermark, allowing the user to
evaluate the method’s performance with respect to alterations. This allows the user to consider
robustness in terms of recoverability, and how each of the methods stand up to various changes
in the image.
To address the issue of invisibility, the GUI allows users to compare images before and
after watermarking. It displays the difference visually and numerically. This same system is
used to allow users to compare images before and after morphological attacks, allowing a wide
spectrum of uses. With time, this GUI would aid in systematically identifying the strengths and
weaknesses of various methods, allowing one to prepare counterattacks against the widest array
of attacks possible.
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26-11-2012, 11:13 AM

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