Annotated Bibliography On Multimedia Security

Annotated Bibliography On Multimedia Security
Multimedia security is ever demanding area of research covering different aspects of electrical
engineering and computer science. In this chapter, our main focus is encryption of JPEG2000
compatible images. Though both stream and block cipher have been investigated in the literature,
but this chapter provides a detailed study of block cipher as applied to images, since JPEG2000
generates various subband sizes as blocks. In the first section, we briefly define various encryption
components like wavelet transform, bit plane decomposition, XOR operation, artificial neural
network, seed key generator and chaotic map functions, for interest of the reader. Later in section 2,
we present literature review of various encryption techniques from two perspectives: applications to
highlight scope of research in this domain; and approaches to provide overall view of multimedia
encryption. The section three provides a new two–layer encryption technique for JPEG2000
compatible images. The first step provides a single layer of encryption using a neural network to
generate a pseudo–random sequence with a 128–bit key, which XORs with bit planes obtained from
image subbands to generate encrypted sequences. The second step develops another layer of
encryption using a cellular neural network with a different 128–bit key to develop sequences with
hyper chaotic behavior. These sequences XOR with selected encrypted bit planes (obtained in step
1) to generate doubly–encrypted bit planes. Finally,
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Steganography Is The Most Effective And Fastest Media For...
In this modern era, the computer and internet have becomes the most effective and fastest media for
communication that connect different parts of the global world. As a result, people can easily
exchange information and share information with the others via the internet. However, the
information security requires the confidential data that needs to be protected from the unauthorized
users. Steganography is one of the methods used for the secure transmission of confidential
information. It can provide a high level of security to secure the important data during combined
with encryption. Steganography is a Greek origin word that means stegos meaning cover and grafia
to which classified as cover writing. Steganography is hiding a secret message into other
information such as sound, image and video. It is also known as invisible communication. In
addition, steganography is related to two technologies which are watermarking and fingerprinting.
Both these technologies provide the same goals which are mainly used for intellectual property
protection.Thus, both are different in algorithm requirements. Watermarking provides a hidden
copyright protection by owner whereas the fingerprinting used a copy of the carrier object and make
it as unique to the different customer. Besides, image steganography is a collection of numbers that
hide information or message inside the image. In this image hidden method, the pixels of the image
are changed to hide the secret data and invisible to

Content-Based Image Retrieval Case Study
INTRODUCTION
Pertaining to the tremendous growth of digitalization in the past decade in areas of healthcare,
administration, art & commerce and academia, large collections of digital images have been created.
Many of these collections are the product of digitizing existing collections of analog photographs,
diagrams, drawings, paintings, and prints with which the problem of managing large databases and
its repossession based on user specifications came into the picture. Due to the incredible rate, at
which the size of image and video collection is growing, it is eminent to skip the subjective task of
manual keyword indexing and to pave the way for the ambitious and challenging idea of the
contend–based description of imagery.
Many ... Show more content on Helpwriting.net ...
In this paper, we will be looking at different methods for comparative study of the state of the art
image processing techniques stated below (K means clustering, wavelet transforms and DiVI
approach) which consider attributes like color, shape and texture for image retrieval which helps us
in solving the problem of managing image databases easier.
Figure 1: Traditional Content–Based Image Retrieval System
LITERATURE SURVEY–
DiVI– Diversity and Visually–Interactive Method
Aimed at reducing the semantic gap in CBIR systems, the Diversity and Visually–Interactive (DiVI)
method [2] combines diversity and visual data mining techniques to improve retrieval efficiency. It
includes the user into the processing path, to interactively distort the search space in the image
description process, forcing the elements that he/she considers more similar to be closer and
elements considered less similar to be farther in the search space. Thus, DiVI allows inducing in the
space the intuitive perception of similarity lacking in the numeric evaluation of the distance
function. It also allows the user to express his/her diversity preference for a query, reducing the
effort to analyze the result when too many similar images are returned.
Figure 2: Pipeline of DiVI processing embedded in a CBIR–based tool.
Processing of

Image Processing Essay
4.1 INTRODUCTION
In image processing, noise reduction and restoration of image is expected to enhance the qualitative
inspection of an image and the performance criteria of quantitative image analysis methods Digital
image is inclined to a variety of noise which attribute the quality of image. The main purpose of de–
noising the image is to reinstate the detail of original image as much as possible. The criteria of the
noise removal problem depends on the noise type by which the image is contaminated .In the field
of reducing the image noise variously type of linear and non linear filtering techniques have been
proposed . Different approaches for reduction of noise and image betterment have been considered,
each of which has their own ... Show more content on Helpwriting.net ...
4.2 DISCRETE COSINE TRANSFORM
DCT expresses a finite sequence of data points in terms of the sum of a cosine function oscillating at
different frequencies. DCT is Fourier–related Transform similar to DFT, but using only real
numbers. It is used for image comparison in frequency domain. DCT is more robust to various
image processing technique like filtering, bluing brightness and contrast adjustment etc. although
these are decrepit to geometric attacks like rotation, scaling, cropping etc. it is used in JPEG
compression.
DCTs are generally related to Fourier series coefficients of a periodically and symmetrically
extended sequence. In DCT an image can be broken down into three different frequency bands High
frequency components block (FH), Middle frequency components block (FM) and Low frequency
components block (FL). First of all image is segmented into non overlapping blocks of 8x8. Then
every of those blocks ahead DCT is implemented. After that some block selection criteria is applied
and then coefficient selection criteria is applied. y(j,k)=√(2/M) √(2/N) α_j α_k ∑_(x=0)^(M–
1)▒∑_(y=0)^(N–1)▒〖{x(m,n)*cos⁡
〖((2m+1)jπ)/2M〗 cos⁡
〖((2n+1)kπ)/2N〗}〗 (4.1) α_j={█(1/
√2@1)┤ j=0 or j=1,2,......,N–1 (4.2) 〖

An Efficient Distributed Arithmetic Architecture For...
An Efficient Distributed Arithmetic Architecture for
Discrete Wavelet Transform in JPEG2000 encoder
R.Karthik1, K.Jaikumar2
1, 2 Asst. Professor, Department of ECE, P. A. College of Engineering and Technology, Pollachi.
1 karthikasprof@gmail.com
2 jaikumarkarthi@gmail.com
Abstract –– The JPEG 2000 image compression standard is designed for a broad range of data
compression applications. The Discrete Wavelet Transformation (DWT) is central to the signal
analysis and is important in JPEG 2000 and is quite susceptible to computer–induced errors.
However, advancements in Field Programmable Gate Arrays (FPGAs) provide a new vital option
for the efficient implementation of DSP algorithms. The main goal of project is to design multiplier
less and high speed digital filters to design DWT. The convolution and lifting based approach posses
hardware complexity due to multiplier and long critical paths. The Distributed arithmetic
architecture is implemented to achieve multiplier less computation in DWT filtering, it is based on
Look–up table approach, which may lead to a reduction of power consumption and the hardware
complexity. DA is basically a bit–serial computational operation that forms an inner product of a
pair of vectors in a single direct step. To speed up the process the parallel DA is implemented. In the
parallel implementation, the input is applied sample by sample in a bit parallel form.
Index terms JPEG 2000, DWT, Error Detection, DA. INTRODUCTION
In the last few

Advantages And Disadvantages Of Discrete Wavelet Transform
Discrete Wavelet Transform DWT is a frequency based transform which is performed on wavelets.
It can be 1–D, 2–D and etc. It divides an image into four sub–bands, namely  LL (Low resolution
image)  HL (Horizontal)  LH (vertical)  HH (diagonal) This division can be performed up to
many levels. It captures not only notion of frequency content but also temporal content. Wavelets
provide a mathematical way of encoding information in such a way that it is layered according to
level of detail. DWT is more computationally efficient than other transformations because of its
excellent localization properties. Wavelets are capable of complete lossless reconstruction of
image[6]. Advantages of DWT 1. No need to divide the input coding into ... Show more content on
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Three levels of rotations have been implemented. First the original watermarked image is being
rotated by 90o , then 180o and at last the image is being rotated by 270o in clock wise direction.
Gaussian noise On digital image Gaussian noise can be reduced using a spatial filter, though when
smoothing an image, an undesirable outcome may result in the blurring of fine–scaled image edges
and details because they also correspond to blocked high frequencies. Image compression Image
compression may be lossy or lossless. Lossless compression is preferred for archival purposes and
often for medical imaging, technical drawings, clip art, or comics. Lossy compression methods,
especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially
suitable for natural images such as photographs in applications. Salt–and–pepper Noise Salt–and–
pepper noise is an attack for which a certain amount of the pixels in the image are either black or
white (hence the name of the noise). Salt–and–pepper noise can be used to model defects in the
transmission of the image that a pixel is corrupted. Additive

The Human Visual System ( Hvs ) For More Secure And...
Research in the field of watermarking is flourishing providing techniques to protect copyright of
intellectual property. Among the
various methods that exploits the characteristics of the Human Visual System (HVS) for more
secure and effective data hiding,
wavelet based watermarking techniques shows to be immune to attacks, adding the quality of
robustness to protect the hidden
message of third party modifications. In this paper, we introduced non blind with DWT & SVD .
Also we applies a casting
operation of a binary message onto the wavelet coefficients of colored images decomposed at
multilevel resolution.
1.Introduction
There has been an explosive growth in use of internet and World Wide Web and also in multimedia
technology and
it's applications recently. This has facilitated the distribution of the digital contents over the internet.
Digital
multimedia works (video, audio and images) become available for retransmission, reproduction, and
publishing over
the Internet. A large amount of digital data is duplicated and distributed without the owner's consent.
This arises a
real need for protection against unauthorized copy and distribution. Hence it became necessary to
build some secure
techniques for legal distribution of these digital contents. Digital Watermarking has proved to be a
good solution to

tackle these problems. It discourages the copyright violation and help to determine the authenticity
and ownership of
the data.
A Digital image

Image Compression Using Hybrid Svd Wdr And Svd Aswdr
Image Compression Using Hybrid SVD–WDR and SVD–ASWDR: A comparative analysis
Kanchan Bala
(Research Scholar)
Computer Science andEngineering Dept.
Punjab Technical University
Jalandhar, India kanchukashyap@gmail.com Er. Deepinder Kaur
(Assistant professor)
Computer Science and Engineering Dept.
Punjab Technical University
Jalandhar, India deepinderkaur.bhullar@gmail.com Abstract–––In this paper new image
compression techniques are presented by using existing techniques such as Singular value
decomposition, wavelet difference reduction (WDR) and Adaptive wavelet difference reduction
(ASWDR). The SVD has been taken as a standard technique to hybrid with WDR and ASWDR.
Firstly SVD is combined with WDR (SVD–WDR) and after that it is combined with its advance
version that is ASWDR (SVD–ASWDR) in order to achieve better image quality and higher
compression rate. These two techniques are implemented or tested on several images and results are
compared in terms of PSNR, MSE and CR.
IndexTerms–––Compression rate (CR), Peak signal to noise ratio (PSNR), Mean square error
(MSE), Joint photographic expert group (JPEG2000), Singular value decomposition (SVD), Wavelet
Difference Reduction (WDR).
I. INTRODUCTION
One of the applications of DIP is transmission and encoding. The very first image that was
transmitted over the wire was from London to New York through the medium of a submarine cable.
The picture that was evacuated took three hours to grasp from one place to another.

The Image Coder Block Diagram And Their Respective...
This report would deal with the image coder block diagram and their block functionalities. This
report also deals with wavelet based approximation with the definition of terminologies dealing with
distortions such as MSE, PSNR. This report also deals with assignment tasks to be implemented in
MATLAB to determine the quality of image and the best imaging filter type and number of
decomposition and their respective graphical representation.
II. INTRODUCTION
The wavelet based image coder would generally begin with the process of transformation of image
data from one domain to another domain taking example of a FDCT(Forward Discrete transform)
nothing but a discrete time version of a fourier cosine series. This process would not involve any
losses since it deals with just transformation. The transform must decorrelate in such a manner no
important information of signal is lost. These signals need not be encoded here as they are just being
transformed the main process of compression has to be taken place in the next stage. After the
signals have been transformed the signal have to be quantized making use of quantisation table
wherein at the decoder end these quantization values are multiplied with these signals to retreive the
original or reconstructed information signal. The main process happens at tthis stage called as
compression. The inverse transform does the process of reconstruction the original signal. The
process of quantisation is not invertible and hence the original

Using Kalman Filter Is Digital Signal Processing Based Filter
2.4 VIDEO DENOISING
Nowadays digital cameras which is used to capture images and videos are storing it directly in
digital form. But this digital data ie. images or videos are corrupted by various types of noises. It
may cause due to some disturbances or may be impulse noise. To suppress noise and improve the
image performances we use image processing schemes. In this paper they uses Kalman filter to
remove the impulse noise. The Kalman filter is digital signal processing based filter. It estimates
three states past, present and future of a system.[10] To remove noise from video sequences they
utilize both temporal and spatial information. In the temporal domain, by collecting neighbouring
frames based on similarities of all images, to remove noise from a video tracking sequence they
given a low–rank matrix recovery phenomena. [11]
3. METHODOLOGY ADOPTED
3.1 Wavelength De–noising
3.2 Bilateral De–noising
3.1 WAVELENGTH DENOISING
Basically a wavelet is small wave, which has its energy concentrated in time to give a tool for the
analysis time varying phenomena. It is easier to remove noise from a contaminated 1D or 2D data
using these algorithms to eliminate the small coefficient associated to the noise. In many signals,
mostly concentration of energy is in a small number of dimensions and the coefficients of these
dimensions are relatively large compared to other dimensions (noise) that has its energy spread over
a large number of coefficients. In wavelet thresholding

Secure Patients Data Transmission Using Xor Ciphering...
Secure patients data transmission using XOR ciphering encryption and ECG steganography
Shaheen S.Patel1 Prof. Dr. Mrs.S.V.Sankpal2
1 D.Y.Patil College of Engg and Technology, Kolhapur, Maharashtra
2 Asso. Prof . D.Y. Patil College of Engg and Technology, Kolhapur, Maharashtra.
E–mails: 1shaheenpatel7860@gmail.com , 2sankpal16@yahoo.com
Abstract :–
As no of patients that are suffering from cardiac diseases are increasing very rapidly, it is important
that remote ECG patient monitoring systems should be used as point–of–care (PoC) applications in
hospitals around the world. Therefore, huge amount of ECG signal collected by body sensor
networks from remote patients at homes will be transmitted along with other personal biological
readings such as blood pressure, temperature, glucose level, etc., and get treated accordingly by
those remote patient monitoring systems. It is very important that patient privacy is protected while
data are being transmitted over the public network as well as when they are stored in hospital
servers . In this paper, a one new technique has been introduced which is the hybrid of encryption
and wavelet–based ECG steganography technique . Encryption allows privacy and ECG
steganography allows to hide one sensitive data into other insensitive host thus guaranteeing the
integration between ECG and the rest.
Keywords:–ECG ,encryption ,steganography, authentication,wavelet
I .INTRODUCTION
Population increase has increased number of patients that are

Essay On Medicinal Volume Information Recovery
incorporates three cases, specifically: added substance homomorphism; include homomorphism,
question picture highlight is not encoded; full homomorphism encryption strategy. In [15],
Bellafqira et al. proposed a protected usage of a substance based picture recovery (CBIR) technique
that works with homomorphic scrambled pictures from which it separates wavelet based picture
includes next utilized for ensuing picture examination. Test comes about show it accomplishes
recovery execution on a par with if pictures were prepared nonencrypted.
In this paper, we proposed a powerful calculation of encoded medicinal volume information
recovery in light of DWT (Discrete Wavelet Transform) and DFT (Discrete Fourier Transform).
Since DWT can't avoid ... Show more content on Helpwriting.net ...
B. 3D Discrete Fourier Transform (3D–DFT)Discrete Fourier Transform is an essential change in
the field of picture rocessing. Expecting that the span of the medicinal volume information is M * N
* P, at that point the three–dimensional Discrete Fourier Transform (3D–DFT) is characterized as
takes after:
M −1 N −1 P −1
F ( u , v , w )  ¦ f ( x , y , z ) ⋅e − j 2 π xu/M e − j 2 π yv/N e− j 2 π zw/P
x = 0 y = 0 z = 0 
u = 0,1, , M − 1; v = 0,1, , N − 1; w = 0,1, , P − 1;
The equation of Inverse Discrete Fourier Transform(3D–
IDFT) is as per the following:
1 M −1 N −1 P−1
f ( x, y, z) = ¦¦¦F (u, v, w) ⋅e j 2π xu/M e j 2π yv/N ej 2π zw/P
MNP u =0 v =0 w=0
x = 0,1, , M − 1; y = 0,1, , N − 1; z = 0,1, , P − 1;
Where f(x,y,z) is the testing an incentive in the spatial area, F(u,v,w) is the inspecting an incentive in

the recurrence space.
C. Calculated Map
Calculated guide is the most average and broadly utilized tumultuous framework, which is a one–
dimensional disorderly framework. Calculated Map is a nonlinear guide given by the accompanying
equation:
[ N + = μ [ N − [ N
Where 0 μ ≤ 4 is the branch parameter, xk ∈ 0,1 is
the framework variable,the emphasis numberis K.
At the point when μ ≤ , the framework will demonstrate a disorganized

An Effective System For Lossless Image Compression
Abstract – In this paper, we proposed an effective system for lossless image compression using
different wavelet transform such as the stationary wavelet transform, the non decimated wavelet
transform, and discrete wavelet transform with delta encoding and compare the results without delta
encoding. With the development in the field of networking in the process of sending and receiving
files needed to effective techniques for image compression as the raw images required large
amounts of disk space to defect during transportation and storage operations. We used lossless
compression to maintain the original features of the image in this process; there is a major problem
which often is low compression ratios. We also use three types of wavelet transform which are
discrete wavelet transform, non decimated wavelet transform, and stationary wavelet transform to
demonstrate the effectiveness of the proposed system for comparison and to show the differences
between each type to overcome previous challenges. This paper proposed a system for lossless
image compression based on the use of the three types of wavelet transforms using Arithmetic
coding and Huffman coding with delta coding, which helps in the high compression ratio to clarify
the extent of the difference and distinction between each type. The results show that the stationary
wavelet transform outperforms the non decimated wavelet transform and the discrete wavelet
transform and with delta encoding outperforms without delta

Advantages And Disadvantages Of Wavelets
Wavelets, based on time–scale representations, provide an alternative to time–frequency
representation based signal processing. Wavelets are then represented by dilation equations, as
opposed to difference or differential equations. Wavelets maintain orthogonality with respect to their
dilations and translations. Orthogonality of wavelets with respect to dilations leads to multigrid
representation. Wavelets decompose the signal at one level of approximation into approximation and
detail signals at the next level. Thus subsequent levels can add more detail to the information
content. The perfect reconstruction property of the analysis and synthesis wavelets and the absence
of perceptual degradation at the block boundaries favor use of wavelets ... Show more content on
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The same procedure is adapted to obtain one level 2–D DWT by using two vertical filters as shown
in Fig. 1. Implementation results are discussed in section 4. The advantage of flipping method is it
requires only four multipliers and eight adders instead of eight multipliers and four adders to
implement 9/7 filter compare to lifting scheme. Main disadvantage of flipping is serial operation. In
1–D DWT of FA, odd and even input samples are processed by five blocks namely , , , ,
(1 &2)in the cascade manner.1 &2are scaling blocks. Since the output from one block is
fed as the input to the next block, the maximum rate at which the input can be fed to the system
depends on the sum of the delays in all four stages. The speed may be increased by introducing
pipelining at the points indicated by dotted lines Fig.3. In this case, the input rate is determined by
the largest delay among all four blocks.The delay in the individual stages may be reduced further by
using constant coefficient multiplier (KCM) which uses a look up table (LUT) for finding the
product of a constant and a variable. 2.2 Modified Flipping Architecture Modified flipping
architecture (MFA) is implemented using MBW–PKCM technique.

Steganography Analysis : Steganography And Steganography
1.1 Steganography and its introduction Steganography comes from the Greek word
"Steganographia" (στεγανό–ς, γραφ–ειν) which means "covered writing". It is the art and science of
concealing a secret information within a cover media preventing unauthorized people to know that
something is hidden in it, so that the message can only be detected by its intended recipient.
Cryptography and Steganography are ways of secure data transfer over the Internet
1.1.1 Cryptography and Steganography
Cryptography scrambles a message to conceal its contents; steganography hides the existence of a
message. It is not sufficient to simply encrypt the message over network, as attackers would detect,
and react to, the presence of enciphered communications. But when information hiding is used, even
if an eavesdropper snoops the transmitted object, he cannot suspect the secret information in the
communication since it is carried out in a concealed way.
1.1.2 Limitations of Cryptography over Steganography
One of the main drawbacks of cryptography is that the outsider is always aware of the
communication because of the incomprehensible nature of the text. Steganography overthrows this
drawback by concealing information into an unsuspicious cover object. Steganography gained
importance because the US and the British government, after the advent of 9/11, banned the use of
cryptography and publishing sector wanted to hide copyright marks. Modern steganography is
generally understood to deal

Secure Patients Data Transmission Using
Secure patients data transmission using XOR ciphering encryption and
ECG steganography
Shaheen S.Patel1 Prof Dr Mrs.S.V.Sankpal2 A. N. Jadhav3
1 D.Y.Patil College of Engg and Technology, Kolhapur, Maharashtra
E–mails: 1shaheenpatel7860@gmail.com , 2sankpal16@yahoo.com, 3ajitsinhj33@gmail.com
Abstract :–
As no of patients that are suffering from cardiac diseases are increasing very rapidly, it is important
that remote ECG patient monitoring systems should be used as point–of–care (PoC) applications in
hospitals around the world. Therefore, huge amount of ECG signal collected by body sensor
networks from remote patients at homes will be transmitted along with other personal biological
readings such as blood pressure, temperature, glucose level, etc., and get treated accordingly by
those remote patient monitoring systems. It is very important that patient privacy is protected while
data are being transmitted over the public network as well as when they are stored in hospital
servers . In this paper, a one new technique has been introduced which is the hybrid of encryption
and wavelet–based ECG steganography technique .
Encryption allows privacy and ECG steganography allows to hide one sensitive data into other
insensitive host thus guaranteeing the integration between ECG and the rest.
Keywords:–ECG ,encryption

Image Assessment Models Of Image Quality Assessment Methods
Kai Zeng et al. have worked on perception evaluation. Authors have used multi–solarization image
fusion algorithms. In this research first authors have build a database that contains source input
images with multiple exposure levels(>= 3) together with fuse images generated by both standard
and new image fusion algorithms. In this research, image fusion is active in the last ten years and a
valid number of image fusion and objective image quality assessment methods have been proposed.
In this paper, authors have been allocated the evaluation and comparison of classical and standard
multi exposure fusion(MEF) and relevant image quality assessment. In this research current work is
that none of the traditional and standard objective of ... Show more content on Helpwriting.net ...
Registration in levels are done. After pre–filtering apply the 2D–DMWT to the registered input
images. They have appoint different weights to multi–wavelet coefficient using an activity level
measurement. After that grouping is done and coefficient selection is done then consistence
verification is done. At last inverse discrete multi–wavelets Transform is applied and post filter is
used. After that we get fused image. In this paper authors have showed that qualitatively multi–
wavelet transform give better performance than wavelet and this can be happen with proper
selection of multi–wavelet transform.[19] Mirajkar Pradnya P. and Sachin D. Ruikar have proposed
an image fusion approach based on stationary wavelet transform. This method is firstly applied with
the original image to get an edge image frequency measurement properties in level1 and level2 both.
After that this result is compared with some other methods. 2D SWT Method is based on the idea of
no decimation. In this paper author have calculated the performance results of used fusion method
that provides good result. In addition to this that algorithm can be applied to other feature in noisy
image source.[20] M. Hossny and S. Nahavandi have proposed the duality between image fusion
algorithm and quality metrics. The authors have proposed duality index as main function against
which combination of fusion

India has always been known for its rich cultural...
India has always been known for its rich cultural diversity. There are tens of thousands of literature
work written in different languages. These work are sometimes required to be converted into digital
form for portability and convenience. Script Identification of Indian languages has always been a
challenging task due to similarity that occur between the scripts. The challenge is even deepened
when distinguishing a language which uses the same script. For example the Bangla script is used to
write Assamese, Bengali and Manipuri languages. There are various known techniques which have
been used for the problem. These techniques are broadly classified under local and global
approaches. Though global techniques are known for their less ... Show more content on
Helpwriting.net ...
These reasons ensure the demand for hard copy documents. Engineers are tackling ways to create
intelligent software which can automatically analyze, extract, convert and store the text from these
documents and digitize it for editing, transferring and resource efficient storing. This field of
engineering falls into a general heading under the sub–domain of Digital Signal Processing called,
Document image analysis, which has been a fast growing and challenging research area in recent
years. Most of the Optical Character Recognition (OCR) system works on a critical assumption on
the script used in the image document that is supplied for recognition. A falsely selected choice of
language or script type will hinder the performance of the OCR system. Therefore human
intervention is required to select the appropriate package related to the supplied documents. This
approach is certainly inappropriate, inefficient, impractical and undesirable. An intermediate process
of script identification is required to be appended after the normal preprocessing step of skew
correction, resizing, cropping and binarization. The output of this script identification process helps
to determine the script used in the documents, and thus human intervention can be eliminated.
Automatic script identification will not only enable to identify the script, but it can be further
implemented for archiving work such as sorting and searching of document image for a

Image Analysis : Gagandeep Kaur And Anand Kumar Mittal
In this paper Gagandeep kaur and Anand Kumar Mittal have proposed a new hybrid technique and
comparison of results of two image using it. They also proposed comparison of new hybrid
algorithm with older. Discrete cosine transform and variance combination with hybrid discrete
wavelet transform. These techniques provides good results in terms of Pseudo signal to noise ratio
and mean square error. [11] Kede ma et al. has worked on the untouched area of perceptual quality
assessment as used for multi–solarization image fusion. The authors have designed multi–
solarization fusion data–list. They analyzed valued difference between the different multi–
solarization image fusion. Findings given by authors are unsuccessful in finding ... Show more
content on Helpwriting.net ...
Proposed method has worked as follows. Firstly, Positron Emission Tomography and Magnetic
Resonance Images are taken as input for preprocessing Positron Emission Tomography images
firstly decomposed into removal of noise and enhancing the input images using Gaussian filter to
sharpen the input images filtering used high or low pass region carries more automatically and
spectral information. This region decomposed by applying four level discrete wavelet transform.
After this authors have combine high frequency coefficient of Positron Emission Tomography and
Magnetic Resonance Images using average method. Similarly by combining low frequency
coefficients of Positron Emission Tomography and Magnetic Resonance Images obtained fuse
results for the low activity region. To get better structural information fuzzy C means clustering
used. For avoiding color distortion color patching is also done. Finally fused image is extracted and
displayed with less color distortion and without losing any structural information. In this research
authors have proposed a new fusion method for fusing Positron Emission Tomography and
Magnetic Resonance Images brain images on discrete wavelet transform with less colour distortion
and without losing any anatomical

Modern Transformers And Electric Power Systems
Large power modern transformers are vital components and very expensive in electric power
systems. Forthwith, it is very important to reduce the duration and frequency of unwanted outages
that results in a high demand imposed on power transformer protection relays, this includes the
requirements of dependability related with no mal–operations, operating speed related with short
fault clearing time to avoid extensive damage or to preserve power quality and power system
stability and security related with no false tripping.
Discrimination between inrush currents and internal faults has long been known as a challenging
power transformer protection problem. Otherwise, inrush currents contain large second harmonic
component compared to internal faults, conventional transformer protection are designed to achieve
required discrimination by sensing that large second harmonic content [1]. The level of second
harmonic component of the inrush current has been reduced due to improving in transformer core
material and occur power system changes. Additionally, a large second harmonic can also be found
in transformer internal fault currents if a shunt capacitor is connected to a transformer in a long extra
high voltage transmission line. Therefore, the methods based on the measurement of the second
harmonic are not sufficiently effective for differential protective relays [2].
Newly, several new protective schemes have been proposed to deal with the previous problem in
large power

Discrete Wavelet Transform For Compressing And...
Discrete Wavelet Transform for Compressing and Decompressing the Speech Signal Bhavana
Pujari1, Prof. S.S.Gundal2 Abstract: The original digital speech signal contains tremendous measure
of memory, the main concept for the speech compression algorithm is presented here, in which bit
rate of the speech signal is reduced with maintaining signal quality for storage, memory saving or
transmission over the long distance. The concentration of this project is to compact the digital
speech signal using Discrete Wavelet Transform and reconstruct same signal using inverse
transform, in .NET. The algorithm of Compression is oriented in three basic operation, they are
apply the DWT, Threshold, Encode the signal for transmission Analysis of compression procedure is
done by comparing the original speech and reconstructed signal. The main advantages of DWT
provides variable compression factor. Keywords: Bit rate, Compression, Decompression, Discrete
Wavelet Transform (DWT), .NET, Threshold. Introduction The Speech is finest effective medium
for viewpoint to face communication and telephony application. Speech coding is the process of
obtaining a compact representation of audio signals for efficient transmission over band–limited
wired and wireless channels and/or storage. The procedure of Compression is done by transferring
an original signal to alternate compressed signal that consist of small amount of memory.
Compression is conceivable simply because information in input data

Essay On Plasma Collisionality
The relationship between plasma collisionality and intermittency has been investigated for density
and potential fluctuations in the stellarator TJ–K, as well as with Hasegawa–Wakatani simulations.
The intermittency level was determined in experiments using two methods. First, the scale separated
kurtosis analysis consisted of applying a wavelet transform to density and potential time series and
calculating the kurtosis of the wavelet coefficients at a chosen frequency scale, (–– removed HTML
––) (–– removed HTML ––) 30 (–– removed HTML ––) (–– removed HTML ––) similar to the
method of calculating the kurtosis of a high–pass filtered signal. (–– removed HTML ––) (––
removed HTML ––) 24 (–– removed HTML ––) (–– removed HTML ––) ... Show more content on
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For density fluctuations, a general trend of increasing intermittency with increasing collisionality is
observed, for both experimental data and simulated data. This trend agrees with the HW simulation
result for the Lagrangian intermittency at high collisionality. (–– removed HTML ––) (–– removed
HTML ––) 12 (–– removed HTML ––) (–– removed HTML ––) For potential fluctuations, on the
other hand, no trend in the intermittency level and collisionality is observed, and the intermittency
level remains low, indicating self–similar fluctuation statistics, in accordance with Refs. (––
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––) , (–– removed HTML ––) 44 (–– removed HTML ––) , and (–– removed HTML ––) 45 (––
removed HTML ––) . This result suggests that potential fluctuations can be modelled using
Gaussian statistics over the parameter range investigated. (–– removed HTML ––) (–– removed
HTML ––) The observed trend in the intermittency level of density fluctuations with collisionality
and the self–similarity of potential fluctuations can be explained in the framework of the HW model.
The model describes the spatio–temporal evolution of the density, potential, and vorticity, with a
parallel coupling term influenced by the collisionality. In the HW simulations, vorticity fluctuations
have been

Images And Images Of Images
INTRODUCTION
1.1 IMAGE
An image is an artifact that depicts or records visual notion, for example a two–dimensional picture,
that has a comparable appearance to some subject – normally a physical object or a person, for this
reason offering an outline of it. Photos may be –dimensional, which includes a photo, display screen
show, and as well as a 3–dimensional, inclusive of a statue or hologram. They may be captured by
optical devices – such as cameras, mirrors, lenses, telescopes, microscopes, and so on. And natural
items and phenomena, consisting of the human eye or water surfaces.
The phrase image is also used inside the broader sense of any –dimensional discern along with a
map, a graph, a pie chart, or an summary painting. on this wider experience, photos also can be
rendered manually, along with by using drawing, portray, carving, rendered mechanically through
printing or laptop pics generation, or evolved with the aid of a combination of techniques, mainly in
a pseudo–photograph.
1.2 IMAGE FUSION
In pc vision, Multi sensor image fusion is the system of combining applicable statistics from two or
extra snap shots right into a single photo. The ensuing picture might be more informative than any
of the enter pictures. Image fusion is the method that mixes statistics from a couple of snap shots of
the identical scene. Those pix may be captured from specific sensors, obtained at unique times, or
having distinctive spatial and spectral characteristics. The item of the

Steganography Essay
Security of information becomes one of the most important factors of information technology and
communication because of the huge rise of the World Wide Web and the copyrights laws.
Cryptography was originated as a technique for securing the confidentiality of information.
Unfortunately, it is sometimes not enough to keep the contents of a message secret, it may also be
necessary to keep the existence of the message secret and the concept responsible for this is called
steganography [2]. Steganography is the practice of hiding secret message within any media. Most
data hiding systems take advantage of human perceptual weaknesses. Steganography is often
confused with cryptography because the two are similar in the way that they both are used to protect
secret information. If both the techniques: cryptography and steganography is used then the
communication becomes double secured [2].The main difference between Steganography and
cryptography is that, cryptography concentrates on keeping the contents of a message secret while
steganography concentrates on keeping the existence of a message secret. ASCII Conversion &
cyclic mathematical function based ... Show more content on Helpwriting.net ...
In the first unit, they decomposed the image to be watermarked in to four dimensional modified
DWT coefficients, by adding pseudo–random codes at the high and middle frequency bands of the
DWT of an image. In the second unit, a key has been generated from LHLH frequency bands of the
4–Level DWT image and this key is watermarked in to the original gray image. In the third unit, for
data compression we used bit plane slicing technique where the original gray image is sliced in to 8
planes and we used bit plane 3 to embed in to the key watermarked image. The embedded key
watermarked image is transmitted and the key watermarks are extracted with

Wavelet Based Protection Scheme For Multi Terminal...
WAVELET BASED PROTECTION SCHEME FOR MULTI TERMINAL TRANSMISSION
SYSTEM WITH PV AND WIND GENERATION
Y Manju Sree1 Ravi kumar Goli2 V.Ramaiah3
Assistant Professor Professor Professor Manju547sree@gmail.com goli.ravikumar@yahoo.com
ramaiahvkits@gmail.com
1,2,3 Kakatiya Institute of Technology & Science, Warangal
Abstract: A hybrid generation is a part of large power system in which number of sources usually
attached to a power electronic converter and loads are clustered can operate independent of the main
power system. The protection scheme is crucial against faults based on traditional over current
protection since there are adequate problems due to fault currents in the mode of operation. This
paper adopts a new approach for detection, discrimination of the faults for multi terminal
transmission line protection in presence of hybrid generation. Transient current based protection
scheme is developed with discrete wavelet transform. Fault indices of all phase currents at all
terminals are obtained by analyzing the detail coefficients of current signals using bior 1.5 mother
wavelet. This scheme is tested for different types of faults and is found effective for detection and
discrimination of fault with various fault inception angle and fault impedance.
Keywords: Multi terminal transmission System, Wavelets, Hybrid energy sources.
1. INTRODUCTION
An electrical power system consists of utility grid and hybrid

Image Denoising Essay
3.1 IMAGE DENOISING
Denoising of image means, suppressing the effect of noise to an extent that the resultant image
becomes acceptable. The spatial domain or transform (frequency) domain filtering can be used for
this purpose. There is one to one correspondence between linear spatial filters and filters in the
frequency domain. However, spatial filters offer considerably more versatility because they can also
be used for non linear filtering, something we cannot do in the frequency domain. Recently wavelet
transform is also being used to remove the impulse noise from noisy images. Historically, in early
days filters were used uniformly on the entire image without discriminating between the noisy and
noise–free pixels. mean filter such as ... Show more content on Helpwriting.net ...
Researchers published different ways to compute the parameters for the thresholding of wavelet
coefficients. Data adaptive thresholds were introduced to achieve optimum value of threshold. Later
efforts found that substantial improvements in perceptual quality could be obtained by translation
invariant methods based on thresholding of an Undecimated Wavelet Transform . These
thresholding techniques were applied to the nonorthogonal wavelet coefficients to reduce artifacts.
Multiwavelets were also used to achieve similar results. Probabilistic models using the statistical
properties of the wavelet coefficient seemed to outperform the thresholding techniques and gained
ground. Recently, much effort has been devoted to Bayesian denoising in Wavelet domain. Hidden
Markov Models and Gaussian Scale Mixtures have also become popular and more research
continues to be published. Tree Structures ordering the wavelet coefficients based on their
magnitude, scale and spatial location have been researched. Data adaptive transforms such as
Independent Component Analysis (ICA) have been explored for sparse shrinkage. The trend
continues to focus on using different statistical models to model the statistical properties of the
wavelet coefficients and its neighbors. Future trend will be towards finding more accurate
probabilistic models for the distribution of non–orthogonal wavelet

Importance Of Subpixel Significance Of Image Correlance
Subpixel correlation of optical imagery is also based on normalized cross correlation. However,
COSI–CORR applies correlation in both spatial and frequencies domain (Yaseen & Anwar, 2013).
This allows a spatial correlation that gives the 2–D displacement. Figure 4.9 and 4.8 shows the
spatial displacement. The black box shows landslide area. These two bands combined gives a vector
field (figure 4.11). This vector field shows the direction of landslide. To achieve a good correlation
is needed. Correlation of image needs several careful decision making. Different parameters can
change the image correlation quality. In figure 4.9 shows the quality of the image correlation. Here,
the result of correlation is not great but it is usable as a ... Show more content on Helpwriting.net ...
A careful look at this gives a view of other landslide area within the image. The figure 4.12 gives us
the holistic view of the target landslide. It is a north–west facing landslide. This matches the aspect
map that shows the landslide location to be on the north–facing slope (figure 2.1). The displacement
measured from SAR analysis to be 193m (after dividing with the step size 3) and from the optical
subpixel correlation, the displacement is calculated to be 148m (after dividing with the step size 4).
The displacement is measured as the length of the landslide. The list of limitations faced in this
study is quite large. From data acquisition to analysis, several constraints has been met during this
study. First, the SAR image that is freely available that gives the temporal coverage of the landslide
in question is Sentinel 1A. This satellite instrument captures SAR image using C–band which uses
5–7 cm wavelength and 5.35 GHz frequency (Alsdorf et al., 2007; Potin, 2013). This c–band cannot
pierce the vegetation canopy to reach ground (Moran et al., 1998). This lead to some decorrelation
in the image as the study area is a highly vegetated area. One Previous study used corner reflector
for better result while measuring slow onset landslide movement (Sun & Muller, 2016).
Nonetheless, in this study, no corner reflectors were used, as the landslide was rapid onset and there
were no previously CRs installed in that area.

A Literature Study Of Robust Color Image Watermarking...
A LITERATURE STUDY OF ROBUST COLOR IMAGE WATERMARKING ALGORITHM
PANKAJ SONI 1, VANDANA TRIPATI2, RITESH PANDEY3
1. Dept of ECE, ME student, G.N.C.S.G.I., JABALPUR, M.P., INDIA,
2–Dept of ECE, Asst. Prof., G.N.C.S.G.I., JABALPUR, M.P., INDIA,
2–Dept of ECE, Asst. Prof., G.N.C.S.G.I., JABALPUR, M.P., INDIA,
ABSTRACT: Digital Watermarking is a technology which is used to identify the owner, distributor
of a given image. In recent years, digital watermarking plays a vital role in providing the appropriate
solution and various researches have been carried out. In this paper, an extensive review of the
literature related to the color image watermarking is presented together with compression by
utilizing an assortment of techniques. The proposed method should provide better security while
transferring the data or messages from one end to the other end. The main objective of the paper is
to hide the message or a secret data into an image which acts as a carrier file having secret data and
to transmit to the intention securely. The watermark can be extracted with minimum error. In terms
of PSNR, the visual quality of the watermarked image is exceptional. The proposed algorithm is
robust to many image attacks and suitable for copyright protection applications.
KEYWORDS: Watermarking, Discrete wavelet transform, Discrete Cosine Transform, PSNR, MSE.
I. INTRODUCTION
DIGITAL image watermarking has become a necessity in many applications such as data
authentication, broadcast

What Is Fourier Transform
Accordingly, the magnitude of energy density produces the spectrum of function, which is
commonly indicated as color plots. To investigate the signal around time t of interest, window
function has chosen that is peaked around t. Therefore, the modified signal S_t (τ) is short and its
Fourier transform is called short–time Fourier transform (Satish 1998). The principle of STFT is to
divide the initial waveform signal into small segments with short–time window, apply Fourier
transform to each segment. However, due to the signal segmentation, this method has limitation in
time–frequency resolution. It can only be applied to analyze the segmented stationary signal or the
approximate stationary signal, but for the non–stationary signal, when ... Show more content on
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A continuous wavelet transform is expressed as: Where x(t)is the waveform signal, a is the scale
parameter, b is the time parameter and ψ(t)is the mother wavelet, which is a zero mean oscillatory
function centred around zero with a finite energy,∫_(–∞)^(+∞)▒〖ψ(t)dt=0〗, and "*" denotes
complex conjugate. By dilating via the scale parameter a and translations via the time parameter b,
wavelet transform of a waveform signal decomposes the signal to a number of oscillatory functions
with different frequencies and time (Jardine 2006). Similar as Fourier transform decomposes a
signal into a series of complex sinusoids, the wavelet transform decomposes a signal into a family of
wavelets. The difference is that sinusoids are smooth, symmetric, and regular but wavelets can be
ether symmetric or asymmetric, sharp or smooth, regular or irregular. The dilated and translated
versions of a prototype function are contained in the family of wavelets. The prototype function is
defined as a mother wavelet. The scale parameter a and time parameter b of wavelets formulate how
the mother wavelet dilates and translates along the time or space axis. Different types of wavelets
can be chosen for different forms of signals to best match the features of the signal. The flexibility
of selecting wavelets and the characteristic of wavelets make wavelet transform a beneficial tool for
obtaining reliable results and

Comparing Vector Quantization and Wavelet Coefficients Essays
Wavelet transform is efficient tool for image compression,
Wavelet transform gives multiresolution image decomposition. which can .be exploited through
vector quantization to achieve high compression ratio. For vector quantization of wavelet
coefficients vectors are formed by either coefficients at same level, different location or different
level, same location.
This paper compares the two methods and shows that because of wavelet properties, vector
quantization can still improve compression results by coding only important vectors for
reconstruction. Thus giving priority to the important vectors higher compression can be achieved at
better quality. The algorithm is also useful for embedded vector quantization coding of wavelet ...
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Image and Video Coding 1905
Methodl
PSNR I C band technique. Cross band technique takes the advantages of nterband dependency and
improves compression.
If we take into consideration HVS response, all the coefficients are not important for image
representation. This visual redundancy can be removed to improve the compression ratio further [5].
Edges in the image are more imponant for good quality image reconstruction. Vectors giving edge
information are more important .Giving priority to such important vectors embedded coding can be
achieved.
Method 2
PSNR I C
' . PRIORITY BASED ENCODING
Wavelet decomposition represents edges in horizontal vertical and diagonal direction. If we code
only the coefficients representing edges, image reconstruction at reduced rate is possible. To find
edge region, variance of the adjacent coefficients can be considered. In vector quantization if the
vectors are formed with adjacent coefficients from the same band at same
Location, variance of the vectors represent edge region.
Quality of the reconstructed image by coding only high variance vectors is much better than
interband vector quantiation. Codebook is generated including high variance vectors from training
images. This results into close match for important vectors and improves quality [6].
This simple

Techniques Used For The Real Time Applications Is On The...
Vital challenge in the real time applications is on the face recognition through different illumination.
Despite of numerous illuminations filtering techniques are in place, the concepts are said to be
archaic and the critical analysis of performance of illumination filtering techniques are not covered
[1, 2]. Based on the current face recognition tech–niques that come with a group function to
normalize the illumination help to facilitate the critical challenge in the face recognition system [3].
Most of the techniques used in photometric normalization were used to develop the methods used in
this particular toolbox [4]. Those are the techniques used for carrying out the normalization of
illumi–nation prior to the actual processing stage. One could see that it is in contrary with the
methods applied in compensating the appearances induced by illumination at the classi–fication or
modelling stage [5, 6].
2 Illumination Normalization Face Recognition
Illumination variation. Basically, these methods can be classified into three main categories. Fig 15
showed of Taxonomy of filtering of illumination.
Illumination normalization
Illumination modeling
Illumination invariant feature extraction.
2.1 Illumination normalization:
Primary category refers to the normalized face images under illumination variation. The typical
algorithms for this category are Wavelet, Steerable filtering, Non–local Means based also adop–tive
Non–local means.
2.1.1Wavelet–based (WA)
Du and Ward

Electronic Identification Based On The Identity Of Human...
Signatures continue to be an important biometric for authenticating the identity of human beings and
reducing forgeries. The major challenging aspect of automated signature identification and
verification has been, for a long time, a true motivation for researchers. Research into signature
verification has been vigorously pursued for a number of years and is still being explored, especially
in the offline mode. In this paper, we have discussed a brief overview of offline signature
verification techniques for reducing forgeries and some of the most relevant perspectives are
highlighted.
Identity verification based on the dynamic signatures is commonly known issue of biometrics. This
process is usually done using methods belonging to one of three approaches: global approach, local
function based approach and regional function based approach. In this paper we focus on global
features based approach which uses the so called global features extracted from the signatures. We
present a new method of global features selection, which are used in the training and classification
phase in a context of an individual. Proposed method bases on the evolutionary algorithm.
Moreover, in the classification phase we propose a flexible neuro–fuzzy classifier of the Mamdani
type.
Fig1:– Offline Signature verification system
Old framework for offline signature verification. Different from previous methods, our approach
makes use of online handwriting other than 2D signature images for

Denoising Of Computer Tomography Images Using Wavelet...
Denoising of Computer Tomography images using Wavelet based Multiple Thresholds Switching
(WMTS) filter
Mayank Chakraverty1 *, Ritaban Chakravarty2, Vinay Babu3 and Kinshuk Gupta4
1Semiconductor Research & Development Center, IBM, Bangalore, Karnataka, India
2New Jersey Institute of Technology, NJ, USA
3 Invntree, Bangalore, Karnataka, India
4 Indian Space Research Organization (ISRO) Satellite Centre, Bangalore, Karnataka, India
1nanomayank@yahoo.com, 2ritaban.87@gmail.com, 3vinaygbabu@gmail.com,
4kinshuk.chandigarh@gmail.com
ABSTRACT Computer Topography images are often corrupted by salt and pepper noise during
image acquisition and /or transmission, reconstruction due to a number of non–idealities
encountered in image sensors and communication channels. Noise is considered to be the number
one limiting factor of CT image quality. A novel decision–based filter, called the wavelet based
multiple thresholds switching (WMTS) filter, is used to restore images corrupted by salt–pepper
impulse noise. The filter is based on a detection–estimation strategy. The salt and pepper noise
detection algorithm is used before the filtering process, and therefore only the noise–corrupted
pixels are replaced with the estimated central noise–free ordered mean value in the current filter
window. The new impulse detector, which uses multiple thresholds with multiple neighborhood
information of the signal in the filter window, is very precise, while avoiding an undue increase in

Characteristics Of The Watermarking System
the CSF characteristics of the HVS in order to embed the watermarking data on selected wavelet
coefficients of the input image. The selected coefficients dwell on the detail sub bands and the
information about the edges of the image were contained in them. Hence, the embedded information
becomes invisible by exploiting the HVS which was less sensitive to alterations on high frequencies.
The success of their method in terms of robustness and transparency was illustrated by results of the
experiments conducted. Their approach performed against the diverse widespread signal processing
methods as compression, filtering, noise and cropping splendidly.
A scaling based image–adaptive watermarking system which ... Show more content on
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An adaptive image watermarking algorithm based on HMM in wavelet domain was presented by
Zhang Rong– Yue et al. [27]. The algorithm considered both the energy correlation across the scale
and the different sub bands at the same level of the wavelet pyramid and employed a vector HMM
model. Intended for the HMM tree structure, they optimized an embedding strategy. They enhanced
the performance by employing the dynamical threshold schemes. The performance of the HMM
based watermarking algorithm against Stir mark attacks, such as JPEG compression, adding noise,
median cut and filter was radically enhanced.
A multi–resolution watermarking method based on the discrete wavelet transform for copyright
protection of digital images was presented by Zolghadrasli and S. Rezazadeh [21]. The watermark
employed was a noise type Gaussian sequence. Watermark components were added to the
significant coefficients of each selected sub band by considering the human visual system in order to
embed the watermark robustly and imperceptibly. They enhanced the HVS model by performing
some small modifications. The extraction of the watermark involved the host image. They measured
the similarities of extracted watermarks using the Normalized Correlation Function. The robustness
of their method against wide variety of attacks was illustrated.
An entropy–based method for

Taking a Look at Audio Compression
Audio compression is most important strategies in multimedia applications in recent years. In
communication, the main objective is to communicate without noise and loss of information. This
paper emphasis the enhanced lossless compression and noise suppression in mobile phones and
hearing aids. An effective technique is needed to transfer the audio signals with reduced bandwidth
and storage space, without noise and loss of information in the signal during compression. Wavelet
transformation method produces better lossless compression than other methods. The proposed
method uses Haar wavelet and the algorithm used for lossless compression and noise reduction are:
MLT–PSPIHT ( Modulated Lapped Transform–Perceptual Set Partitioning In Hierarchical Trees)
and HANC (Hybrid Active Noise Cancelling) algorithm.
Keywords: Audio lossless compression, noise suppression, Haar wavelet, MLT–SPIHT algorithm,
HANC algorithm.
INTRODUCTION:
Audio compression technique is increasingly becomes more significant in multimedia applications,
since it produce extensively reduced bit rate than the original signal, the bandwidth , storage space
and expense for the transmission of audio signal is also reduced correspondingly.
General frame work of audio compression
In specific to the multimedia application, the suppression of noise and the compression with no loss
of data is most mandatory in the use of mobile phones and hearing aids. Due to the transmission of
signal along with the noises like

The Digital Of Digital Image
There has been an explosive growth in use of internet and World Wide Web and also in multimedia
technology and it's applications recently. This has facilitated the distribution of the digital contents
over the internet. Digital multimedia works (video, audio and images) become available for
retransmission, reproduction, and publishing over the Internet. A large amount of digital data is
duplicated and distributed without the owner's consent. This arises a real need for protection against
unauthorized copy and distribution. Hence it became necessary to build some secure techniques for
legal distribution of these digital contents. Digital Watermarking has proved to be a good solution to
tackle these problems. It discourages the copyright violation and help to determine the authenticity
and ownership of the data.
A Digital image watermarking systems have been proposed as an efficient means for copyright
protection & authentication of digital image content against unintended manipulation (spatial
chromatic). Watermarking techniques tries to hide a message related to the actual content of the
digital signal, watermarking is used for providing a kind of security for various type of data (it may
be image, audio, video, etc). Digital watermarking generally falls into the visible watermarking
technology and hidden watermarking technology visible and invisible watermarks both serve to
deter theft but they do so in very different ways.
Watermarking is identified as a major technology

A Literature Study Of Watermarking Techniques On Contrast...
A LITERATURE STUDY OF WATERMARKING TECHNIQUES ON CONTRAST
ENHANCEMENT OF COLOR IMAGES Rajendra Kumar Mehra1, Amit Mishra2 1. Dept of ECE,
M–TECH student, VITS, JABALPUR, M.P., INDIA, 2. Dept of ECE, H.O.D., VITS, JABALPUR,
M.P., INDIA. ABSTRACT: In this paper a watermarking method with contrast enhancement is
presented for digital images. Digital Watermarking is a technology which is used to identify the
owner, distributor of a given image. If the watermarked images is low contrast & poor visual quality
or due to poor illumination in some imaging system, the contrasts of the obtained images are often
needs to be improve. In recent years, digital watermarking plays a vital role in providing the
appropriate solution and various researches have been carried out. In this paper, an extensive review
of the literature related to the color image watermarking is presented together with contrast
enhancement by utilizing an assortment of techniques. This method outperforms other present
algorithm by enhancing the contrast of images well without introducing undesirable artifacts.
KEYWORDS: Watermarking, Histogram equalization, CLAHE, CAHE, PSNR, MSE. I.
INTRODUCTION DIGITAL image watermarking has become a necessity in many applications
such as data authentication, broadcast monitoring on the Internet and ownership identification.
Various watermarking schemes have been proposed to protect the copyright information. There are
three indispensable, yet contrasting requirements for a

Essay On Image Annotation
CHAPTER 4 ALGORITHM & IMPLEMENTATION 4.1 Implementation Here we introduce
effective data hiding for image annotation, High fidelity is a demanding requirement for data hiding
for images with artistic or medical value. This correspondence proposes image watermarking for
annotation with robustness to moderate distortion. To achieve the high fidelity of the embedded
image, the model is built by mixing the outputs from entropy and a differential localized standard
deviation filter. The mixture is then low–pass filtered and normalized to provide a model that
produces substantially better perceptual hi–fidelity than existing tools of similar complexity. The
model is built by embedding two basic watermarks: a pilot watermark that locate ... Show more
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4.3 Introduction The proposed model combines the outputs of two simple filters: entropy and a
differential standard deviation filter to estimate visual sensitivity to noise. The two outputs are
mixed using a non–linear function and a smoothing low–pass filter in a post–processing step. As a
result, image localities with sharp edges of arbitrary shape as well as uniformly or smoothly colored
areas are distinguished as "highly sensitive to noise," whereas areas with noisy texture are identified
as "tolerant to noise." This ability can be particularly appealing to several applications such as
Compression, de–noising, or watermarking. In this paper, we focus on the latter one with an
objective to create a tool that annotates images with 32 bits of meta–data. Note that we do not
impose any security requirements for the watermarking technology [4]. The developed
watermarking technology embeds two watermarks, a strong direct–sequence spread spectrum (SS)
watermark tiled over the image in the lapped bi–orthogonal transform (LBT) domain [5]. This
watermark only signals the existence of the meta–data. Next, we embed the meta–data bits using a
regional statistic quantization method. The quantization noise is optimized to improve the strength
of the SS watermark while obeying the constraints imposed by the perceptual model. We built the
watermarks to be particularly robust to aggressive JPEG compression and

Strengths Of Steganography
Abstract– Steganography is a technique of hiding the secret information. Steganography hides the
existence of the secret data and make the communication undetectable. Secret data can be
communicated in an appropriate multimedia carrier such as image, audio or video. Image
steganography is extensively used technique. In this technique secret data is embedded within the
image. Steganography techniques can be categorized into two groups – adaptive and non–adaptive.
Each of these have its strengths and weaknesses. Adaptive steganography embeds the secret
information in the image by adapting some of the local features of the image. Non–adaptive
steganography embeds secret data equally in each and every pixel of the image. Several techniques
have been proposed for hiding the ... Show more content on Helpwriting.net ...
Still, message transmissions over the Internet need to face a few issues, for example, copyright
control, information security, and so on. Consequently we need secure secret specialized strategies
for transmitting message over the Internet. Encryption is a surely understood strategy for security
insurance, which alludes to the process of encoding secret data in such an approach, that just the
person with the right key can effectively decode it. In any case, encryption makes the message
unreadable, and making message sufficiently suspicious to pull eavesdroppers' consideration.
Another approach to tackle this issue is to conceal the mystery data behind a cover with the goal that
it draws no extraordinary consideration. This strategy of data security is called steganography
(Petitcolas and Anderson,1998; Petitcolas and Katzenbeisser, 2000) in which imperceptible
communication happen. The cover could be a digital picture and the cover image after embedding is
called stego–picture. Attackers don't have the foggiest idea about that the stego–image has concealed
mystery information, so they won't mean to get the mystery information from the

Annotated Bibliography On Multimedia Security

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