chapter 1 introduction - inflibnet...
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CHAPTER 1
INTRODUCTION
1.1 GENERAL
The protection of intellectual property has become a major problem
in the digital age. The ease of copying digital information without any loss of
quality violates the conservation of mass property of traditional media, which
inhibited wide global distribution in the past. On the Internet today, it is
possible to duplicate digital information a million-fold and distribute it over
the entire world in seconds. These issues worry creators of intellectual
property to the point that they do not even consider to publish on the Internet.
More information is transmitted in a digital format now than ever, and the
growth in this trend cannot be estimated in the future. Digital information is
susceptible to be copied at the same quality as the original. A watermark is a
pattern of bits inserted into a digital image, audio or video file that identifies
the file's copyright information (author, rights, etc.). The name “watermark” is
derived from the faintly visible marks imprinted on the organizational
stationary.
During the 18th century watermarks began to be used as anti-
imitation measures on money and other documents. When sharing
information on the internet, digital watermark approaches are of great
demand. While distributing information through online, we never know if
someone uses them without our knowledge. The owner should be able to hide
some information in the digital file and extract information to prove his
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ownership when the need arises. Watermarking system can be viewed as a
communication system consisting of three main elements: an embedded, a
communication channel and a detector. To make use of the Human Visible
System (HVS), various watermarking techniques have been developed.
Figure 1.1 shows a general watermarking life cycle. Tracking of
reproduced copies, prevention of illegal copying and validating the digital
data can be done by the watermark. Insertion of a watermark, detection of a
watermark and removal of a watermark are the three main processes involved
in a watermarking system.
Figure 1.1 General watermarking life cycle
Important characteristics of the watermark are invisibility,
robustness, readability and security (Ming-Shing et al 2001, Sin and sung
2001). Requirement for digital watermarks are 1) deterioration of the quality
of digital content is minimized 2) watermarks are retained and detectable after
the digital content is edited, compressed, or converted 3) the structure of a
watermark makes it difficult to detect or overwrite (alter) the embedded
information (watermark contents) 4) processing required for watermarking
and detection is simple 5) watermark information embedded in digital content
can be detected as required and 6) embedded watermark information cannot
Secure Part – Transmitter In secure Part
Secure Part – Receiver
Attacks
Original Image
EmbeddingScheme
Embedding
Detection
Retrieval
Decoding
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be eliminated without diminishing the quality of the digital content that
carries the watermark.
1.2 CLASSIFICATION OF WATERMARK
General classification of the watermark is shown in Figure 1.2.
Watermarking is classified based on working domain, type of document,
human perception and application. Watermarking techniques are divided into
four categories in accordance with the type of information (document) to be
watermarked (Laurence and Ahmed 1996). They are text watermarking,
image watermarking, audio watermarking and video watermarking. In text
watermarking, the text documents can be watermarked by patterning the inter-
word spaces. Text watermarking is primarily of three types: Line Shift
Coding (LSC), Word Shift Coding (WSC) and Feature Coding (FC). These
methods require the original unmarked text for decoding.
Figure 1.2 General classification of watermarking
WATERMARKING
According To Human Perception
According To Working Domain
According To Application
Spatial Domain
Frequency Domain
Invisible
Visible Source Based
Destination Based
Robust Fragile
Private Public Quasi-invertible
Invertible Non-invertible
Non quasi-invertible
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In image watermarking technique, the watermark image is applied
into a host image for security. Image watermarking is nothing but the still
image watermark. A continuous frame of image is called as video and the
watermarking process is known as video watermarking. Digital video
watermarking uses the inherent properties of digital images, with the
limitations of human vision to insert invisible data into digital video to
provide copyright protection. Based on the visibility of the resultant image,
the digital watermarks can be divided into two different categories viz. visible
watermark and invisible watermark. Visible watermark is a secondary
translucent overlaid into the primary image but in an invisible digital
watermarking, information is added as digital data.
In the case of audio watermarking, to hide the watermark and make it
inaudible, watermarking uses the time and frequency masking properties of
the human ear. Echo hiding is one of the techniques which involve hiding
information within the recorded sound by introducing very short echoes.
Invisible digital watermark is further divided into private and public
watermarking. In private watermarking or informed watermarking, the
original image is required to perform the extraction process. In public
watermarking or blind watermarking, the original image is not required to
perform the extraction process. In the public watermarking process,
watermarked images are seriously destroyed and the detection of watermarked
image is very difficult. Because of this, blind watermarking technique is used
for visible watermarking.
Based on the ability of the watermark to resist attack, watermarks
are categorized into two types. They are fragile watermark and robust
watermark. Random image processing methods can readily destroy the fragile
watermarks. Most of the image processing methods are robust and can be
extracted from heavily attacked watermarked image without destroying the
image. This makes the robust watermark to be preferred in copyright
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protection. Invisible–robust watermark is embedded in such a way that the
alterations made to the pixel value are perceptually not detected and it can be
recovered only with appropriate decoding mechanism. Invisible–fragile
watermark embedding process of the image would alter or destroy the
watermark. Watermarking techniques are frequently used in the still camera
images, medical images and satellite images where the copyright protection is
required by the users.
A digital image is usually represented by a two-dimensional image.
Depending on the image resolution, an image may be a vector or a raster in
type. Digital image usually refers to raster images and it is also called as
bitmap images. Various available digital image file types are Joint
Photographic Groups (JPG), Graphic Interchange Format (GIF), Tagged
Image File Format (TIFF), Portable Network Graphics (PNG), and Bitmap
(BMP). TIFF is a very flexible format that can be lossless or lossy. PNG is a
lossless storage format; it can be used to compress the file size. The
compression is exactly reversible, so the image is recovered exactly. GIF is
lossless only for images with 256 colour or less. JPG works by analyzing
images and discarding kinds of information. BMP is an uncompressed
proprietary format.
Digital Still Camera (DSC) records the image data in the form of
document, specified as the standard file format. Nowadays, digital documents
can be distributed via the World Wide Web (WWW) to a large number of
people in a cost-efficient way. There is a strong need for security services in
order to keep the distribution of digital multimedia work both profitable for
the document owner and reliable for the customer. Watermarking technology
plays an important role in securing the business as it allows placing an
imperceptible mark in the multimedia data to identify the legitimate owner,
track authorized users via fingerprinting (Dittmann 1999) or detect malicious
tampering of the document (Kundur and Hatzinakos 1998).
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Patient records are stored in hospitals in digital format (Electronic
Patient Records (EPR)) for more than 20 years. Medical image has three
binding security characteristics, such as confidentiality, availability and
reliability. In our proposed work on confidentiality, we use public key.
Availability can be proved by decoding the watermarked image by using
normal procedure. Reliability will be proved by the information which cannot
be modified by an unauthorized person. Reliability is of much importance as
degradation of the image content will lead to serious problems such as wrong
diagnosis of a patient by the doctor. Thus, watermarking is important in case
of medical images for determining authenticity.
Remote sensing satellite images are important sources of
geographical data. Geographical data are commonly used to classify earth
land cover, analyze crop conditions, assess mineral, petroleum deposits, and
quantify urban growth. Contrast stretching, flipping and format conversion
are the attacks that easily remove the watermark image in a satellite image.
An effective watermarking technique for satellite images should have the
following features: The watermark should be imperceptible to the naked eye.
The watermark must be indelible, at least without visibly degrading the
original image. Retrieval of the watermark should explicitly identify the
owner. The watermarking technique should not distort certain specific areas
in the image. Stir mark is commonly used to evaluate the robustness of an
image (Evelyn et al 2009).
1.3 WATERMARKING TECHNIQUES
Digital image watermarking schemes mainly fall into two broad
categories: spatial domain and frequency domain techniques. Visible
watermarking mainly uses spatial domain which requires less computation
and are easy to implement in software as well as hardware. A spatial domain
technique slightly modifies the pixels. However, there must be tradeoffs
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between invisibility and robustness, and it is hard to resist common image
processing and noise. Some of the spatial domain modulation techniques are
Least Significant Bit (LSB), Spread Spectrum Method (SSM). In LSB, the
watermarks are embedded in the least significant bit of the selected pixels of
an image. This method is easy to implement and it is not very robust against
attacks. SSM based watermarking algorithms embed the information by
linearly combining the host image with a small pseudo noise signal, which is
modulated by the embedded watermark.
Compared to spatial domain methods, frequency domain methods
are more widely applied. In frequency domain, the characteristics of the HVS
are better captured by the spectral coefficients. For example, HVS is more
sensitive to low frequency coefficients and less sensitive to high frequency
coefficients. Low frequency coefficients are perceptually significant, which
means alterations to those components might cause severe distortion to the
original image. On the other hand, high frequency coefficients are considered
insignificant and hence the processing techniques, such as compression, tend
to remove high frequency coefficients assertively. To obtain a balance
between imperceptibility and robustness, most watermark algorithms are
embedded in the midrange frequencies. Commonly used frequency domain
techniques are DCT, Discrete Fourier Transform (DFT) and Discrete Wavelet
Transform (DWT).
DCT based watermarking techniques are robust compared to spatial
domain techniques. DCT algorithms are robust against simple image
processing operations like low pass filtering, brightness and contrast
adjustment, blurring, etc. DCT watermarking techniques are difficult to
implement and are computationally more expensive. They are also weak
against geometric attacks like rotation, scaling, cropping, etc. DCT
watermarking can be classified into global DCT watermarking and block
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based DCT watermarking. DCT based watermarking are affected by two
factors. The first fact is that the most important visual part of the image lies at
low frequency sub-band. The second fact is that high frequency components
of the images are usually removed through compression and noise attacks.
DCT watermark is therefore embedded by modifying the coefficients of the
middle frequency sub-band. DFT of a function gives quantitative results of
the frequency content in terms of magnitude and phase. This result is more
important for processing and analysis of signals and images. The DWT is
currently used in a wide variety of signal processing applications, such as in
audio and video compression, removal of noise in audio, and the simulation of
wireless antenna distribution (Evelyn et al 2009). In wavelets, basal functions
are used to represent the signal. DWT is very suitable to identify the areas in
the host image, where the watermark image can be embedded. Wavelets have
their energy concentrated in time and are well suited for the analysis of
transient and time-varying signals.
Watermarking techniques have got a number of applications. Some
of the significant applications are fingerprint, prevention of unauthorized
copying, image authentication, data security, digital media management,
medical area and copyright protection. Copyright protection is probably the
most common use of watermarks today. Copyright owner information is
embedded in the image in order to prevent others from alleging ownership of
the image. Copyright-related applications based on robust watermarking
techniques were discussed by many researchers like Barni et al (2002),
Moulin and Ivanovic (2003), Sebe and Domingo (2003), Trappe et al (2003).
Medical reports play a very important role in the treatments offered to the
patient. A mix up in the reports of two patients could lead to a disaster. To
avoid this problem, visible watermarking technique is used to print the names
of the patients on the X-ray or Magnetic Resonance Image (MRI) scan
reports. Fragile or semi-fragile watermarks are usually selected for
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watermarking process in medical, forensic and intelligence or military
applications (Barreto et al 2002, Li and Yang 2003, Li 2004, Wong and
Memom 2000, Xie and Arce 2001).
In data encryption (embedding), techniques of digital watermarking
do not follow with the same capability because listening, accessing and
viewing the content cannot be prevented. For this reason, digital
watermarking is not protected from hacker attacks (Yeung et al 1998). Some
of the intentional attacks on watermarks are active, passive, forgery and
collusion attacks (Cox et al 2000). In active attacks, the hacker removes the
watermark or makes it undetectable. In passive attacks, the hacker can easily
identify the presence of watermark in the original image without any damage
or removal. The hacker attempts to embed a valid watermark of their own
rather than removing the original watermark in forgery attacks. One piece of
the media is replicated into several copies, each with a different watermark, in
order to construct a copy with no watermark due to collusion attacks.
1.4 PERFORMANCE ANALYSIS
Performance analysis is needed to determine the characteristics of
the watermarking technique such as imperceptible, indelible, statistically
undetectable and easily decodable. Popular metrics used for evaluating
imperceptibility of the watermark are Signal-to-Noise Ratio (SNR) and Peak
Signal-to-Noise Ratio (PSNR), which are based on Mean Square Error (MSE)
between the original and watermarked images. Image manipulation tool (stir
mark) is used to measure the effectiveness of watermark embedding technique
in terms of its robustness and data integrity criteria. Pixel based visual
distortion metrics (Kutter and Petitcolas 1999) are used for performance
analysis to test the image quality between the original and the watermarked
images.
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Correlation coefficient is essential for mapping and ranging
purposes. Individual quality measures are not reliably associated with the
strength of treatment effect in medical areas. Although the use of specific
quality measures may be appropriate in specific well-defined areas of the
medical field, it cannot be generalized to all clinical areas or meta-analysis
(Pan et al 2004). Normalized Correlation Coordinate (NCC) computes the
similarity measurement between the original watermark and the extracted
watermark. Image Fidelity (IF) is a process used to deliver an image
accurately, without any distortion or information loss. IF output depends upon
the ability to detect the difference between images (Klimeck et al 2002). If the
difference between an original image and a compressed one cannot be
detected, then it is concluded that the compression is a lossless compression.
SNR measures are easy to estimate the quality of a reconstructed image
compared to the original image.
Peak signal of the reconstructed watermark image is measured by
PSNR. PSNR values are measured in decibels. Typical PSNR values range
between 20dB and 40dB. The actual value is not meaningful, but the
comparison between two values for different reconstructed images gives a
measure of quality. MSE gives the results of degradation, which was
introduced at the pixel level. The higher MSE shows more degradation.
Accuracy Rate (AR) is used to measure the difference between the original
watermark and the recovered one. AR is computed as follows: AR= CP/ NP.
Where NP is the number of pixels in the original watermark and CP is the
number of correct pixels.
1.5 PROBLEM FORMULATION
This thesis aims at developing an efficient hardware architecture for
the implementation of visible watermarking technique in both spatial domain
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and frequency domain and also aims at the performance analysis of the
algorithm used for invisible watermarking technique using MATLAB 7.6.
The vector based visible digital image watermarking algorithm
using 1D-DCT is tested and implemented with reduced computational
complexity and resource utility involving the scaling
embedding
computational complexity. With this implementation, the speed and
throughput are increased. In biomedical applications, small distortions in the
host image make more problems while diagnosing the diseases. On focusing
biomedical applications, a new block based visible image watermarking
algorithm is developed. In block based a fast 1D-DCT is used to reduce the
resource utilization. In addition, a new mathematical model is introduced to
find the values of scaling and embedding factors. Quality image can be
obtained by means of combining various watermarking techniques. A new
watermarking system is designed to combine the spatial and the frequency
domain techniques.
For the above proposed works, we developed a novel high
performance VLSI architecture implemented on FPGA, simulated in Xilinx
ISE 10.1 and tested in Xilinx Virtex V XC5V1X330 technology. In order to
achieve high throughput and speed, the architectures are designed with the
implementation of pipelining and parallelism techniques.
The hardware architecture designed is applied for visible
watermarking technique only. In order to touch the other category of
watermarking, namely the invisible watermarking, a movement based
watermarking algorithm is developed. The performance analysis of this
algorithm is obtained using MATLAB 7.6.
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Initially, the performance analysis of both visible and invisible
watermarking scheme were computed using the software MATLAB 7.6 and
the evaluation of the works based on synthesis were done using the Xilinx
tool ISE 10.1. Finally, the throughput for visible watermarking is compared
with that of the existing hardware implementation.
1.6 THESIS ORGANIZATION
Chapter 2, “Literature review”, presents a detailed literature review
of the digital watermarking, the existing watermarking algorithms and the
spatial and frequency domain watermarking techniques. It also presents the
reviews related to the hardware implementations.
Chapter 3, “Design and VLSI implementation of vector based
visible image watermark using 1D-DCT”, describes the architecture design
for vector based digital image watermarking. For this, the algorithm is
designed to aim at reducing the computational complexity involving the
embedding and scaling factors prominently used in any visible watermarking
technique.
Chapter 4, “High performance VLSI architecture for block based
visible image watermarking”, explains VLSI architecture design and
implementation of block based visible image watermarking algorithm and its
performance analysis. The fast 1D-DCT for watermarking process is
introduced to facilitate the hardware implementation.
Chapter 5, “Design and implementation of hybrid VLSI
architecture for visible spatial and frequency domain watermarking”,
describes VLSI architecture design and implementation of visible spatial and
frequency domain watermarking algorithms and their performance analysis.
Based on choice of watermark, the process is done either as a pixel by pixel
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operation under spatial domain or as a vector form of operation under
frequency domain.
Chapter 6, “Performance analysis for geometrical attacks on digital
image watermarking”, describes performance analysis for geometrical attacks
on digital invisible image watermarking. Here, the irreversible watermarking
approach robust to affine transform attacks is used. In this approach,
watermark embedding and extraction are carried out with respect to an image
normalized to meet a set of predefined moment criteria.
Chapter 7, “Conclusion”, summarizes the contribution of this thesis
by the implementation of the three proposed approaches in the hardware, the
algorithm proposed for invisible watermarking and its performance
evaluation. Suggestions for future work are also included.