Analysis Of Watermarked Images Using Steganography

Analysis Of Watermarked Images Using Steganography
ANALYSIS OF WATERMARKED IMAGES USING STEGANOGRAPHY BY MEANS OF
ENCRYPTION AND DECRYPTION PROCESS
Priyanka Malvi1Anubhav Sharma2
Address for correspondence
1M Tech scholar, Department of Computer science engineering, Acropolis Institute of Tech.&
Research Bhopal, M.P., India 2Assistant Professor, Department of Computer Science Engineering
Acropolis Institute of Tech.& Research Bhopal, M.P., India
1Email id:priyankas1829@gmail. Contact No.: 9406258135
2Email id:,Hodit.aitr@gmail.com
________________________________________
ABSTRACT
Watermarking is the process of embedding new data into image, audio or video. Digital
Watermarking technique is used to hide a secret or personal message to protect a products copyright
or to demonstrate data integrity. To provide double protection, after the watermarking process, the
watermarked image tends to go through an encryption process using CHAKRA – symmetry key
encryption algorithm which encrypts the data with the concepts of Cartesian coordinate geometry
and circle generation. In this paper, we perform watermarking on different types of images like
BMP, JPEG etc.., and the input image is pre–processed and converted into JPEG–LS format which
contains enhanced quality.
Keywords : JPEG Steganography, uniform embedding, distortion function
design.________________________________________
1.INTRODUCTION
Digital Watermarking technique is used to hide a small image in jpeg, jpg, bmp image of data in a
digital signal in such a way
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Summary : ' Subcarrier Allocation ' Square
Figure 3.6 Waveforms of the QPSK mapping. 3.1.4 Subcarrier Allocation There are three reasons
for outlining the "Subcarrier Allocation" square. The principal is to apportion the information and
pilot subcarriers, the second is to embed invalid subcarriers which conveys "zero" data, and the third
is to execute the FFT shift. After this square, 64 inputs for IFFT are readied. The execution module
is portrayed in Figure 3.7. Two 64 x 16 double port irregular access recollections (RAMs) are
utilized. The invalid subcarriers are accomplished by characterizing the substance of the two RAMs
at relative locations to be zeros. Ports An of the RAMs are utilized for information transporter
composing, while ports B are committed for pilot composing and the 64–subcarrier perusing. They
are controlled by two counters. "Counter_We_48" square stores the 48 information transporter
positions. As per the locations indicated by it, the I and Q estimations of the information images are
built into two RAMs from ports A. In the meantime, FFT movement is inalienably performed.
"Counter_Rd_64" utilizes a counter to create the perusing locations of ports B. At the point when
ports B are empowered and "Counter_Rd_64" tallies from 0 to 63, the coveted 64 inputs for IFFT
are yielded and the "en_ifft" is high, telling the IFFT square to perform figuring. Figure 3.7
Implementation module of Subcarrier Allocation. The perusing ought to begin after the written work
is done. In this way, the yield of

Controlling Robot With Speech Recognition
A MAJOR PROJECT REPORT ON CONTROLLING ROBOT WITH SPEECH RECOGNITION
SUBMITTED IN PARTIAL FULFILLMENT OF THE DEGREE BACHELOR IN TECHNOLOGY
OF ELECTRONICS AND COMMUNICATION ENGINEERING Submitted By: Under the
Supervision of HITESH MATHUR (9911102230) MR. AMIT SINGHAL ASHISH GOEL
(9911102194) AYUSH GUPTA (9911102229) DEPARTMENT OF ECE JAYPEE INSTITUTE OF
INFORMATION TECHNOLOGY, NOIDA (U.P) June , 2015 CERTIFICATE This is to affirm that
the work contained in this report titled as "CONTROLLING ROBOT WITH SPEECH
RECOGNITION" by Hitesh Mathur (9911102230), Ashish Goel (9911102194) and Ayush Gupta
(9911102199) in fractional satisfaction of the course work prerequisite of Bachelor of Technology in
Electronics and communication Engineering , Jaypee Institute of Information Technology, Noida is
a bonafide work did by them under my direction and supervision. The matter submitted in this
report has not been conceded for a recompense of whatever other degree anyplace unless
unequivocally referenced. Signed: Mr. Amit Singhal Project Supervisor ECE Department JIIT, Sec–
128, Noida, ABSTRACT In today 's reality, Robotics is a quickly developing and fascinating field.
Robot has adequate insight to cover the most extreme territory of gave space. We are showing a
Speech Control Robot For Robot control, which is controlled by utilizing discourse controller that is

An Program Records The Voice
This program records the voice
'Get ready to record the voice '
%Read data of letter "a" sound
f1=wavread( 'vc_a ',22050);
%Transform the data using Fast Fourier Transform function
F1=fft(f1,11025);
%Compute to obtain the Normalized Power Spectrum Density of the
%transformed data
Pf1 = F1.* conj(F1)/11025;
Pf1 = transpose(Pf1); %Transpose
Pf1 = Pf1(1:2206); %Only the first 2206 sample data needed
f2=wavread( 'vc_a2 ',22050);
F2=fft(f2,11025);
Pf2 = F2.* conj(F2)/11025;
Pf2 = transpose(Pf2);
Pf2 = Pf2(1:2206);
f3=wavread( 'vc_a3 ',22050);
F3=fft(f3,11025);

Pf3 = F3.* conj(F3)/11025;
Pf3 = Pf3(1:2206);
%Compute the average of the three
Pf_AVG1 = (Pf1 + Pf2 + Pf3) / 3;
%Plot PSD of sound "a"
f = 100000*(0:2205)/22050; %Frequency range
mel = frq2mel(f);
figure(1);
plot(mel,Pf_AVG1);
title( 'The PSD of the Letter "a" Sound ');
xlabel( 'Frequency (Mel) ');
ylabel( 'Power ');
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
%Read data of letter "e" and "o" sounds also by neural networks
f4=wavread( 'vc_e ',22050);
F4=fft(f4,11025);
Pf4 = F4.* conj(F4)/11025;
Pf4 = Pf4(1:2206);
f5=wavread( 'vc_e2 ',22050);
F5=fft(f5,11025);
Pf5 = F5.* conj(F5)/11025;

Pf5 = Pf5(1:2206);
f6=wavread( 'vc_e3 ',22050);
F6=fft(f6,11025);
Pf6 = F6.* conj(F6)/11025;
Pf6 = Pf6(1:2206);
Pf_AVG2 = (Pf4 + Pf5 + Pf6) / 3;
figure(2);

Design Of An Optimized Compressive Sensing
Abstract– This paper presents the design of an optimized Compressive Sensing (CS) based image
compression technique for data transmission over mobile wireless noisy channel. The proposed
technique is more robust to channel noise. It uses individual measurement driven coding scheme,
which facilitates simpler encoder design. The shift of computational burden from encoder to
decoder is more suitable for mobile devices applications where computational power and battery life
are limited. This paper also presents a novel quantizer which allows the encoder to dynamically
adapt to the channel conditions and provide optimum performance.
Keywords–compressive sensing; coding with feedback; image transmission; quantization
I. INTRODUCTION
Wireless spectrum is becoming increasingly scarce as more and more mobile devices are being used
with new innovations to support multimedia applications. The evolution of new applications is
further eroding the ability to make spectrum available to ever increasing mobile users [1]. The
design of mobile devices for inclusion of new and evolving multimedia applications faces big
challenges due to: a) limited power supply from battery; b) wireless transmission impairments for
sustained video transmissions; and c) limited CPU capability in each device. Thus data compression
for wireless networks is becoming more and more important. This research takes image as a sample
multimedia data type to explore the necessary improvement. Traditional image

Advantage And Disadvantage Of Multicarrier Transmission
3.1 Introduction Multicarrier transmission, also known as OFDM is a technique with a long history
back to 1960that has recently seen rising popularity in wireless and wire line. In the recent interest
in this technique is mainly due to the recent advances in digital signal processing technology. The
International standards making use of OFDM for high–speed wireless communications are already
established or being established by IEEE 802.11, IEEE, 802.16, IEEE 802.20 and ETSIBRAN
committees. For wireless applications, an OFDM–based system can be of interest because it
provides greater immunity to multipath fading, and impulse noise, in eliminates the need for
equalizers, efficient hardware implementation can be realized using FFT techniques. ... Show more
content on Helpwriting.net ...
The OFDM makes single–frequency networks possible, which is especially attractive for
broadcasting applications. 3.1.2 Disadvantages of OFDM Transmission: In the OFDM is more
sensitive to frequency offset and phase noise. In OFDM has a relatively large peak–to–average–
power ratio, which tends to reduce the power efficiency of the radio frequency (RF) amplifier. 3.1.3
Application of OFDM During the past decade, OFDM has been adopted in many wireless
communication standards networks, including European digital audio broadcasting system, and
terrestrial digital video broadcasting, and satellite terrestrial interactive multiservice infrastructure in
China. In addition, OFDM has been considered or approved by many groups are working in IEEE
standard, such as IEEE 802.11a/g/n standard network, IEEE 802.15.3a, and IEEE 802.16d/e. The
applications include wireless local area networks, wireless personal area networks and wireless
metropolitan networks. Currently, OFDMA is being investigated as one of the most promising radio
transmission techniques for LTE of the 3rd Generation Partnership Project (3GPP), International
Mobile Telecommunications–Advanced

Progressive Image Transmission Using Ofdm
PROGRESSIVE IMAGE TRANSMISSION USING OFDM Enrol. No. – 13102288 , 13102216
Name of Student – Aman Pandey, Naman Gogia Name of supervisor(s) – Dr. Abhinav Gupta
December – 2016 Submitted in partial fulfillment of the Degree of Bachelor of Technology
DEPARTMENT OF ELECTRONICS AND COMMUNICATION JAYPEE INSTITUTE OF
INFORMATION TECHNOLOGY, NOIDA TABLE OF CONTENTS Chapter No. Topics Page No.
Certificate from the Supervisor II Acknowledgement III Summary IV List of Figures V List of
Symbols and acronyms VI Chapter–1 Introduction Chapter–2 Background 2.1 – OFDM Basics 2.2
– Overview of This OFDM Simulation Project Chapter 3 – Design and Implementation 3.1 –
Overview 3.2 – System Configurations and Parameters 3.3 – Input and Output Description and
Results B. Tech (Min 2 Chapters) Chapter 6 or more Conclusion Appendices A B C References
(IEEE Format) Publications of the Student 1 2 3 Brief Bio–data (Resume) of Student
CERTIFICATE This is to certify that the work titled "Progressive Image Transmission Using
OFDM" submitted by "Aman Pandey(13102288) and Naman Gogia(13102216)" in partial
fulfillment for the award of degree of Bachelor of Technology of Jaypee Institute of Information
Technology, Noida has been carried out under my supervision. This work has not been submitted
partially or wholly to any other University or Institute for the award of this or any other degree or
diploma. Signature of Supervisor ........................... Name of

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

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

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

Image Processing And Image Enhancement
Abstract
Image enhancement is to process an image, in order to make the result more suitable than original
image for specific application. i.e. the image is enhanced.For that many image enhancement
techniques are used. Appropriate choice of such techniques is very important.Image Enhancement is
simple and it's the area based on digital image processing techniques. It improves the quality of the
images by working with the existing data.
Keywords:
Image processing, Image enhancement
1. Introduction
Image processing is the input image which is converted from one form to another. Digital image
processing plays a vital role in real world applications. Before processing an image, it must be
converted into a digital form.
One of part of the image processing is the image enhancement. The main objective of image
enhancement is to modify attributes of an image to make it more suitable for a given task. Here, one
or more attributes of the image get modified. The main purpose of image enhancement is to bring
out details which are hidden in an image, or to increase the contrast in a low contrast image. It
produces an output image that is better than the original image by changing the pixel's intensity of
the input image. Image enhancement is applied in many fields. For example, medical image
analysis, analysis of images from satellites, Aerial imaging, Satellite imaging, Digital camera
applications, Remote sensing etc.
2.Enhancement Techniques
[1]The enhancement methods are mainly

Edge Detection And Frequency Domain
Edge Detection in Frequency Domain
A comparison between different Filtering techniques in Time and Frequncy Domain
Adithya R H
Department of Electronics and Communication
Sri Jayachamarajendra College of Engineering
Mysore, Karnataka, India rhadithya@gmail.com Akash Sharma
Department of Electronics and Communication
Sri Jayachamarajendra College of Engineering
Mysore, Karnataka, India akashshrm02@gmail.com Abstract–This paper presents a comprehensive
comparison of different high pass filtering techniques for Edge detection in both time domain and
frequency domain. The paper examines various kernels and compares the efficiency of the filtering
technique against the computation time for various sizes of images with various sizes of high–pass
filter kernels. We have made use of Sobel filter as the standard filter kernel against which other
techniques are compared.
Keywords–frequency domain; edge detection; sobel filter; laplacian; gaussian;
I. INTRODUCTION
Image sharpening and smoothening is perhaps one of the most ubiquitously used techniques in any
image processing application. While these are considered inexpensive operations, multiple use of
the same may become computationally intensive, and hence may make the overall application slow.
In this paper we examine and compare the performance of sharpening filters in time–domain and
frequency domain. While there are many apparent computational advantages in converting an image
into frequency domain to apply 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
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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

Dsp Manual
www.jntuworld.com
Department of Electronics and Communication VCET,Hyderabad.
DIGITAL SIGNAL PROCESSING
LAB MANUAL
III YEAR II SEMESTER (ECE)
Prepared by: K. Ashok Kumar Reddy
Department of Electronics & Communications Engineering,
Visvesvaraya College of Engineering & Technology,
Ibrahimpatnam.
Digital Signal Processing Lab Manual
Page 1
www.jntuworld.com
www.jntuworld.com
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD III Year B.Tech.
ECE – II Sem L T/P/D C 0 –/3/2
DIGITAL SIGNAL PROCESSING LAB The programs shall be implemented in software (Using
MATLAB / Lab view / C programming/ Equivalent) and hardware (Using TI / Analog devices /
Motorola / Equivalent DSP ... Show more content on Helpwriting.net ...
Furthermore, it allows you to run such lists of commands such that you pass in data
Digital Signal Processing Lab Manual Page 4
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www.jntuworld.com
and/or get data back out (i.e. the list of commands is like a function in most programming
languages). Once you save a function, it becomes part of your toolbox (i.e. it now looks to you as if
it were part of the basic toolbox that you started with). For those with computer programming
backgrounds: Note that MATLAB runs as an interpretive language (like the old BASIC). That is, it
does not need to be compiled. It simply reads through each line of the function, executes it, and then
goes on to the next line. (In practice, a form of compilation occurs when you first run a function, so
that it can run faster the next time you run it.) MATLAB Windows : MATLAB works with through
three basic windows Command Window : This is the main window .it is characterized by MATLAB
command prompt >> when you launch the application program MATLAB puts you in this window
all commands including those for user–written programs ,are typed in this window at the MATLAB
prompt Graphics window: the output of all graphics commands typed in the command window are
flushed to the graphics or figure window, a separate gray window with white background color the
user can create as many windows as the system memory will allow Edit window: This is where you

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

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

What Is A Four-Distributed Static Compensator
This paper deals with a four–leg distributed static compensator (DSTATCOM) which is used to
solve the current related power quality. An amplitude adaptive notch filter (AANF) is employed for
the reference current extraction of DSTATCOM control scheme because of its simplicity, capability
of frequency and amplitude measuring, appropriate extraction of the fundamental signal, and
insensitivity to the amplitude variation of the input signal. To generate the gate pulses of the
switches, an adaptive hysteresis band current controller is used. In addition, fuzzy logic controllers
are used for a better performance of DSTATCOM under dynamic conditions. The proposed control
algorithm is robust to power disturbances, especially when the main voltage ... Show more content
on Helpwriting.net ...
However, these algorithms generally demonstrate a slow time response. Time–domain algorithms
are based on the instantaneous extraction of harmonic currents/voltages. The common time–domain
control strategies are instantaneous reactive power theory (IRPT) [6] and synchronous reference
frame theory (SRF) [7]. Calculation of active and reactive powers by transforming three–phase
voltages and currents into two phases is the principle of PQ theory, which does not work properly
under non–sinusoidal supply conditions [8]. SRF theory is based on conversion of three–phase
quantities into their corresponding dc components, and low–pass filters (LPFs) are employed for
harmonic filtering which contain a time delay and deteriorate the performance of the controller [9].
Most of the advanced control and signal processing methods are accurate and show a better dynamic
response than the FFT, but a large amount of calculations is required, which does not demonstrate
an excellent performance in frequency–varying conditions [10–13]. Adaptive notch filter (ANF) is
another advanced algorithm which has been introduced as an effective control technique for
extracting reference sinusoidal components from distorted input signal. ANF is capable of changing
the notch frequency suitably by tracking the frequency variations of the input signal [14–16].
To the best knowledge of the authors, the modified notch filter in a

Analysis Of Discrete Cosine Transform Region
1) Segment the picture into non–overlapping blocks of 8x8.
2) Apply forward DCT to every of those blocks.
3) Apply some block selection standards (e.g. HVS). 4) Apply coefficient choice criteria (e.g.
highest).
5) Embedded watermark by means of editing the selected Co–efficient.
6) Apply inverse DCT transform on each block.
In DCT, for embedding the watermark records, we divide the photo into one–of–a–kind frequency
bands. In Figure four FL denotes the bottom frequency element of the block, even as FH denotes the
better frequency component and FM denotes the middle frequency factor which is chosen because
the embedding place. The DCT achieves right robustness in opposition to diverse signal processing
attacks because of the choice of ... Show more content on Helpwriting.net ...
DWT divides the picture into excessive frequency quadrants and coffee frequency quadrants. The
low frequency quadrant is again split into two more parts of high and low frequencies (LF) and this
process is repeated until the signal has been entirely decomposed.
a. The single DWT transformed two dimensional image into four parts:
One component is the LF f the authentic photo, the pinnacle right consists of horizontal info of the
picture, the one bottom left consists of vertical information of the unique image, the bottom right
contains high frequency (HF) of the original image. The LF coefficients are greater sturdy to embed
watermark because it incorporates more statistics of the original image [68]. The reconstruct of the
original image from the decomposed image is performed by IDWT [69]. The DWT are scalable in
nature. DWT more regularly used in DIW due to its tremendous spatial localization and multi
resolution techniques. The remarkable spatial localization assets are very handy to apprehend the
place inside the cowl picture in which the watermark is embedded correctly.
32 Fig. 1.21 Two Level Decomposition
The DWT is carried out at the host picture to decompose the image into 4 non overlapping multi
decision coefficient sets. The coefficients are: Where J is the level of the 2–D DWT, h (n) and g (n)
are the impulse reaction. Figure 6 indicates the schematic diagram of 2D wavelet rework. By

Survey On Digital Image Watermarking Techniques
SURVEY ON DIGITAL IMAGE WATERMARKING TECHNIQUES
V.Belmer Gladson1Y.Sam Josuva2, Dr.R.Balasubramanian3
1Research Scholar, 2 Assistant Professor 3Professor,
Department of Computer Science&Engg, Manonmaniam Sundaranar University, Tamilnadu,
1vbgclassic1984@gmail.com 2sam.joejaki@gmail.com,3rbalus662002@yahoo.com
ABSTRACT– In recent years, digital media are widely popular, their security related issues are
becoming greater importance. Watermarking is the process of hiding digital data in a carrier signal.
Embedding a digital signal such as audio, video or image with the information which cannot be
removed easily is called digital watermarking. Digital watermarking mainly used to verify the
authenticity, integrity of the carrier signal or to show the identity of its owners. In this paper, we
present a survey on various digital watermarking techniques. This paper mainly concentrates a
detailed survey of all watermarking techniques on image watermarking types in today's world.
Index Terms – Digital watermarking, spatial domain, Least Significant Bit (LSB), Frequency
domain, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Discrete
Fourier Transform (DFT).
INTRODUCTION
The term digital watermarking was first emerged in 1993, Tirkel introduce two watermarking
techniques to hide the watermark data in the images [1].In recent years digital media are gaining
widely popular, and their security related issues are becoming greater importance. The protection
and

Wireless Sensor Networks : Data Quality For Better...
Abstract– An outlier is a data value which is significantly deviated from the remaining data. In
Wireless sensor networks (WSNs) outliers are the major issues that affect the inherent
characteristics, such as flexibility, maintenance costs and scalability. The sources of an outliers
include noise, errors, events and malicious attacks on the network. In this paper, we proposed a
Compressive sensing algorithm (also known as compressive sensing, compressive sampling, or
sparse sampling) to detect outliers images obtain from wireless sensors. The objective of this
proposed method is to obtain an outlier degree in images through wireless sensors which provides
the data quality for better selection process. CS theory ... Show more content on Helpwriting.net ...
The ideal wireless sensor is networked and scalable, consumes very little power, is smart and
software programmable, efficient for fast data acquisition, reliable and accurate over the long term,
costs little to purchase and install, and requires no real maintenance.
i. Architecture of Wireless Sensor Network
1. The tiny sensors are deployed all over the implemented background in WSNs.
2. The Networks are usually comprised of few sinks and large quantity of sensor nodes.
3. Sensor nodes are ordered into clusters.
4. Each node has a corresponding cluster header.
5. Each sensor node can sense different parameters such as temperature, smoke and relative
humidity.
6. Nodes location details can be obtained by equipment such as Global Positioning System (GPS) or
Bluetooth.
Figure 1: Block diagram of a Wireless Sensor Network
Sensor nodes can be used for continuous sensing, event detection, event ID, location sensing, and
local control of sensors. We classify the applications in military, environment, health, home and
many commercial areas. It is possible to expand this classification with more categories such as
space exploration, chemical process industries and disaster relief. Most of the sensor network
routing techniques and sensing tasks require the knowledge of location with high accuracy without
losing information. Thus, it is important that a sensor node has a location finding system. A
mobilizer may sometimes be

Video Watermarking : The Media Ownership And Attention...
The rapid invention going in internet usage has resulted in the media ownership and attention
towards intellectual property rights among internet users. In this paper, a Multiwavelet Transform
(MWT) based video encoding is proposed. Video watermarking is the practice of inserting an
encode information known as the watermark, into an original video in an imperceptible approach.
The watermark converts or represents information that can protect the watermarked video, typically
identifying the source or the intended destination of the video. The embedded watermark may be
detected by using a watermark detector, which helps to possible an application to react to the
presence (or absence) of the watermark in a video. However, the watermarked video may be
processed, or attacked, prior to watermark detection. Attacks may remove the fixed watermark or
make the watermark more complicated to detect. A logo watermark is composed in the
uncompressed field of a video. Using IM, the watermark is embedded into the chosen multiwavelet
coefficients by quantizing the coefficients. Scrambled watermarks are generated using a set of secret
keys, and each watermark is embedded in each motionless scene of the video. The multi–wavelet
transform uses two transformations such as Haar transform and Doubchies transform. The work is
done with the help of designed user interface. This method extracts the secret message correctly and
this provides better performance.
Keywords:–
Video, Encoding, Multiwavelet

Designing A New Low Complexity Approximation For Image...
ABSTRACT
We focus on approximate algorithms for the computation of the 8–point DCT. While not computing
the DCT exactly, approximate methods can provide meaningful estimations at low–complexity
requirements. Prominent techniques include the signed discrete cosine transform (SDCT), the
Bouguezel–Ahmad–Swamy (BAS) series of algorithms, and the level–1 approximation by
Lengwehasatit–Orteg. All above mentioned techniques possess extremely low arithmetic
complexities. These techniques have some defaults, So proposed technique is to overcome all the
defaults and performed well compare to above techniques. The aim of this correspondence is to
introduce a new low–complexity DCT approximation for image compression in conjunction with a
... Show more content on Helpwriting.net ...
A digital image is composed of a finite number of elements, each of which has a particular location
and value. These elements are referred to as picture elements, image
Bhargava R Mamidi
(012607138)
California State University
Long beach, California, United States
Bhargavareddy450@gmail.com
elements and pixels. Pixel is most widely used to denote the elements of a digital image.
Images play the single most important role in human perception. Humans are limited to the visual
band of the electromagnetic spectrum, imaging machines cover almost the entire electromagnetic
spectrum, ranging from gamma to radio waves. They can operate on images generated by sources
that humans are not accustomed to associating with images. These include ultrasound, electron
microscopy, and computer–generated images. Thus, digital image processing encompasses a wide
and varied field of applications.
Digital image processing is the use of computer algorithms to perform image processing on digital
images. Digital image processing has the same advantages over analog image processing as digital
signal processing has over analog signal processing it allows a much wider range of algorithms to be
applied to the input data, and can avoid problems such as the build–up of noise and signal distortion
during processing. Image processing is a subclass of signal processing concerned specifically with

The Growth Of Internet Coupled With The Rise Of Multimedia...
Abstract. The growth of internet coupled with the rise in networked infrastructure has resulted in
exponential increase in the multimedia content being shared over the communication networks. The
advancement in technology has resulted in increase in multimedia piracy. This is due to the fact that
it is very easy to copy, duplicate and distributes multimedia content using current day technology. In
such a scenario Digital Rights Management is one of the prominent issues to be dealt with and
tremendous work is going on in this direction round the globe. Digital watermarking and
fingerprinting have emerged as fundamental technologies to cater to DRM issues. These
technologies have been found to be of prominent use in content authentication, copy protection,
copyright control, broadcast monitoring and forensic applications. Various requirements of a digital
watermarking system include Imperceptibility, Robustness, Security, Payload and Computational
complexity. The main requirement of real time DRM systems is lesser computational complexity
and high robustness. This chapter proposes and analyses a robust and computational efficient Image
watermarking technique in spatial domain based on Inter Block Pixel Difference (IBPD). The cover
image is divided into 8×8 non overlapping blocks and difference between intensities of two pixels
of adjacent blocks at predefined positions is calculated. Depending upon the watermark bit to be
embedded; both the pixels are modified to bring the

Measuring Heart Rate With A Smartphone
Measuring Heart Rate with a Smartphone By:Linteng Cai Zhe Cheng 1. ABSTRACT Smart phones
are becoming increasingly popular, its performance is improved fast, low–cost smart phone displays
as the physiological solution was measured with an accuracy and may be used beyond the potential
clinical environment. In this project, we use our fingers covering smartphone camera, filtering and
signal band –pass filter, and the detection signal to calculate the BPM ( beats per minute ) of the
peak. We also need to eliminate noise and smooth results by MATLAB code. 2. INTRODUCTION
Many people are beginning to use smart phones. This is because we can download it can ... Show
more content on Helpwriting.net ...
Finally, it will be a lower cost, if the application we use to measure heart rate. Our aim is to explain
how to measure the application by the camera HR. For some chronic diseases, you have to measure
the frequency of extremely HR . In real life, there are many conditions that may affect the heart
diseases and conditions which can be very complex. If the HR can not be on time monitoring, the
situation would be very, very bad. Measuring heart rate is the basic way to diagnosis of heart
disease. The doctor will use a stethoscope to listen to heart sounds. Sound off in the heart of the
heart valves cardiac cycle, from vibration, chordate tendineae, papillary muscle, ventricular wall
perspective, arterial blood flow in from the storm. Based on the heart sounds, myocardial
contractility, hemodynamic status , vascular resistance and pulmonary artery pressure can be
diagnosed. In the smart phone technology is very suitable for the measurement of the heart beat in a
smartphone. Such as camera, touch screen, CPU, WIFI and a few other things. The phone can help
patient to record their behavior may cause a number of diseases. We can use the phone as a sensor as
the physical information monitor records. It can also be recorded on the human body may affect the
other signal. Because the phone is easy to carry. Therefore, it can provide a convenient carried out
under different environmental measurements, such as home health checks, education environment,
operating rooms, emergency

The Founding Principles Of The Fourier Series
FOURIER SERIES AND ITS SOME APPLICATIONS
P. Sathyabama
Assistant professor,
Department of Mathematics,
Bharath collage of science and management, Thanjavur– 5
Abstract
The Fourier Series, the founding principle behind the field of Fourier Analysis, is an infinite
expansion of a function in terms of sines and cosines.In physics and engineering,expanding
functions in terms of sines and cosines is useful because it allows one to more easily manipulate
functions.In particular, the fields of electronics, quantum mechanics, and electrodynamics all make
heavy use of the Fourier series. Key words: Fourier Transform, Discrete Fourier Transform,
Convolution Transforms
I.INTRODUCTION
The Fourier Series, the founding principle behind the field of Fourier Analysis, is an infinite
expansion of a function in terms of sines and cosines or imaginary exponentials. The series is defied
in its imaginary exponential form as follows: ... Show more content on Helpwriting.net ...
Since sines and cosines (and in turn imaginary exponentials) form an orthogonal set1, this series
converges for any moderately well– behaved function f(x) .Examples of the Fourier Series for
different wave forms are given in figure I.
II.THE FAST FOURIER TRANSFORMS
The Fourier Series is only capable of analyzing the frequency components of certain,
discretefrequencies (integers) of a given function. In order to study the casewhere the frequency
components of the sine and cosineterms are continuous, the concept of the Fourier Transform must
be introduced. The imaginary exponential form of the Fourier Transform is defined as

Essay On Fiber Communication System
There are certain inherent flaws with the optical transmission system like inter–symbol interference
and noise. This distortion is introduced by the narrow bandwidth and some distortions due to the
media through the optical signals travel. The linear transversal filter is used to reduce symbol
interference. The system designed to remove unknown distortion is called an adaptive equalizer. The
corrective measure is to identify the distortion and adjust accordingly with the objective to remove
it. The equalizer can be the supervised or unsupervised type. In the TV or radio Transmission, blind
equalizers are used. The literature survey of analysis of mean square error and space division
multiplexing technique and other system removing the ISI ... Show more content on Helpwriting.net
...
The equalizer converges to higher MSE. The noise PSD directed method iterated over 3000 km
transmission on all six modes and it tends to convergence at same MSE to get the standard –10 dB
normalized MSE (NMSE).The noise PSD directed algorithms require 47 blocks and the
conventional algorithm needs 48 blocks [6]. Sean O¨Arık et.al have proposed Long–haul mode–
division multiplexing (MDM) for adaptive multi–input–multi–output (MIMO) equalization to
reduce for modal crosstalk and modal dispersion. To minimize computational complexity, use
MIMO frequency–domain equalization (FDE).Polarization division multiplexing (PDM) system use
single mode fiber but its transmission effected by noise, fiber nonlinearity and dispersion. In multi–
mode fiber (MMF) with multi–input–multi–output (MIMO) transmission Increasing per–fiber
capacity can be achieved more readily by increasing spatial dimensionality the total number of
dimensions available for multiplexing, including spatial and polarization degrees of freedom
denoted by D. In first case two polarization modes of single mode fiber using D=2. This is made
possible by equalization techniques goes on going up with the upward drift of D and higher group
delay. In second case systems using modedivision multiplexing (MDM) in MMFs (D>2) receiver,
computational complexity increases because of an increase in D and because of the large group
delay (GD) spread

Analyzing The Consumers Generating Inter Harmonic Frequencies
Alexander B. Nassif and Jing Yong [7] have proposed a method to identify the consumers
generating inter harmonic frequencies. The inter–harmonics can be measured by means of
Impedance based approach applied at the metering point. The main idea is that, the inter–harmonic
impedance of the system is much smaller than that of an inter–harmonic generating load. This
method can identify the source of each inter–harmonic component without having to rely solely on
the active power measurement and requires only an approximate value for the inter–harmonic
impedance measured at the metering point. As per references [2], [6], [7], [9] any device with
nonlinear characteristics which derive their input power from a sinusoidal electrical system may be
responsible for injecting harmonic currents & voltages into the electrical system [2, 6, 7, 9 ].
Francisco C. De la rossa [2] have described ,all possible nonlinear loads . Among them few are
Power converters such as Variable frequency drives, DC motor controllers, Cycloconverter, Cranes,
Elevators ,Steel mills, Power supplies, UPS,Battery chargers, Inverters & ARC devices such as
Fluorescent lighting, ARC furnaces, Welding machines. According to authors [2] ,[7] Even linear
loads like power transformers can act nonlinear under saturation conditions. This occurs beyond the
so–called saturation knee of the magnetizing curve of the transformer. [2],[7]. According to author
Joseph S. Subjak [9], Communication interference

Detection System Of Illegal Logging Image Using Matching...
International Journal of Computational Engineering Research||Vol, 03||Issue, 6||
www.ijceronline.com ||June ||2013|| Page 57
Detection System of Illegal Logging Image Using Matching Process With Discrete Cosine
Transform Syafruddin Syarif1, Nadjamuddin Harun2, M. Tola3, M. Wihardi Tjaronge4 1 Student of
Doctoral Program Civil Engineering Hasanuddin University, Makassar Indonesia 1,2,3 Department
of Electrical Engineering, Hasanuddin University, Makassar, Indonesia 4 Department of Civil
Engineering, Hasanuddin University, Makassar, Indonesia
I. INTRODUCTION
Forest has many advantages to human life and the earth as the lungs of the world. In the economic
field, the forestry sector contributes significantly to the national income accounts. The high price of
timber in international market leds to timber exploitation in the early 90 's [S. Syarif, et.al, 2012]. It
encourages illegal logging actifity, which causes adverse effects especially on the economy and
ecology fields. In the economic field, the state revenues declined due to the loss of timber tax and
the chance to produce the high quality products of timber also decreased. In addition, the nature
inbalance causes climate change, declining soil productivity, soil erosion and flooding, habitat
destruction, and loss of biodiversity. To solve the problems, the illegal logging detection system is
urgently needed. In this research, image processing and Discrete Cosine Transform (DCT) are
applied for the detection. Nowadays,

Varied Potentials of Aspergillus Species in Synthesis of...
Conclusions
To conclude, though use of Aspergillus species is common in synthesis of metal nanoparticles, these
five species are not well studied. Among them, A. fischeri confirms a good quality production of
AgNPs at an incredibly low concentration of salt solution used but with more number of bigger
sized particles. However, efforts are underway to optimize the conditions in the process to obtain a
good size and shape morphology. Also, understanding the protein–nanoparticle interactions during
the synthesis mechanism shall guide us to the possibility of utilizing the present system as future
''nano–factories''. We aim to purify and characterize the proteins to comprehend their mode of action
and possible interactions with silver ... Show more content on Helpwriting.net ...
Characterization
Change in color was visually observed in the silver nitrate solution incubated with all five
Aspergillus species. The bio reduction of Ag+ in the aqueous solutions was screened by sampling of
aliquots at different time intervals. Absorption measurements were carried out on Thermo–scientific
UV–Visible Spectrophotometer from 200–800nm, at a resolution of 1 nm. A part of the dried
powdered sample was analysed by X–ray diffractometer as a preliminary confirmative method of
the presence of silver nanoparticles. The X–ray diffractometer (Rigaku Miniflex–11) was operated
at a voltage of 30 kV and a current of 15mA with CuKα radiation (λ=1.5406 Å) and at 2 theta
angles, intensities were recorded from 6°to 60°. To know the size of synthesized silver nanoparticles
(AgNPs), size distribution analysis was performed using dynamic light scattering in aqueous
solution. The hydrodynamic size of the silver nanoparticles was obtained using a Zeta–sizer
(Malvern) instrument applying a 660 nm laser. The software was optimized to report summary
statistics based upon the intensity of light scattered. Two milliliter sample volumes from each
nanosilver dispersion were loaded into glass cuvettes and summary statistics were obtained using
triplicate 2 minutes analyses (total analysis time=6minutes). For Fourier transform

Nt1110 Research Paper
Coursework – part1 Name of student Abdalfettah Asharaa UoB number 14022053 File number 3
Test data a Number of signals 4 f v t Signal 1 72 1 0 Signal 2 281 9 2 Signal 3 456 6 3 491 10 1 Test
data b Number of signals 5 f v t cos or exp? Signal 1 44 7 3 cos Signal 2 299 4 5 cos Signal 3 338
14 6 cos Signal 4 55 10 – exp Signal 5 571 9 – exp Test data c i) Enter your numerical answers in
the boxes below f v t Signal 1 348 13 4 Signal 2 397 11 2.87 ≈ 3 Signal 3 491 3 5.84 ≈ 6 ii) The
same formula that used to analyse the value of "t" in the "test_data_b" is also used in the
"test_data_c". The formula is: Theta= tan–1 (imag/real) t= (Theta x 16)/ π. It is clear that the signal
can be seen in figure 1, is a non–stationary ... Show more content on Helpwriting.net ...
Students are asked to generate BER curves against SNR, and to add at least one of these to their
report, together with 100 to 200 words of description. Marks will be given for output curves that are
smooth and regular, and also for plots that show output over a wide range of SNR. After running the
file or the m–file given in simulation.zip "sim_multiple_hiperlan2a_1.m", got the curve that
displays BER "bit error rat" against SNR "signal to noise ratio". Using BER is to calculate the
performance of the transmitter, the receiver and the channel system. Figure 7 below represents the
BER curve against SNR and the received signal for the default value of SNR (1:10). It is clear that
the curve is not smooth and regular as result of the low value of the SNR and the error or the target
number of the error. Figure 7: The BER curve and the received signal for SNR value of 10. Also,
The BER curve can be improved by the target number of the error. It means that the value of that
number can be adjusted in Error Rate Calculation block in the "commhiperlan2a.mdl" in the
simulation.zip folder. In the previous RER curve in the figure 7, the value of the target number of
error was 1000,

Characterization And Classification On Ultrasound Signals...
Microstructural characterization and classification on ultrasound signals Using DCT transformation
in PCA framework Masoud Vejdannik a, Ali Sadr b a,b School of Electrical Engineering, Iran
University of Science & Technology (IUST), Narmak, Tehran 16844, Iran a
m_vejdannik@yahoo.com, b sadr@iust.ac.ir Abstract Purpose: Method: Results: Conclusions:
Introduction Nb–bearing nickel–based superalloys, like the Inconel 625 alloy studied here, exhibit
an outstanding combination of mechanical properties and resistance to pitting, crevice and
intergranular corrosion due to the stiffening effect of chromium, molybdenum and niobium in its
nickel matrix. These properties make precipitation hardening treatments unnecessary [––]. The
extraordinary ... Show more content on Helpwriting.net ...
This segregation and precipitation of the secondary phases can change the mechanical properties of
the alloy and decrease its resistance to corrosion [––]. In addition, the Nb–rich Laves phase has a
low melting point that causes an increase in the temperature solidification range, making the alloy
susceptible to solidification cracking [––]. However, an adequate selection of the welding conditions
can minimize the formation of the Nb–rich Laves phases and consequently, reduce its susceptibility
to solidification cracking. Therefore, it is also important to investigate the phase transformation
process. Nowadays, researchers are evaluating the use artificial intelligence techniques to
characterize microstructures. For example, Albuquerque, Filho, Cavalcante, and Tavares [––]
quantified the porosity of synthetic materials from optical microscopic images successfully, and the
solution proposed, which was based on an artificial neuronal network (ANN), proved to be more
reliable. Albuquerque, de Alexandria, Cortez, and Tavares [––] characterized the microstructures in
images of nodular, grey, and malleable cast irons using a multilayer perceptron

Biometric Codes Are Used For Recognising A User On The...
Abstract
Biometric systems are used for recognising a user on the basis of biometric traits he have. During
authentication some of the frequently asked questions are "Is he who he claims to be?", "Is he a
valid user for gaining access to the system?". Biometric system answers all these questions by
authenticating the users. Every second information is shared and transferred between people and it
is important to make sure that what is sent by sender is what received by the receiver thus raising
the demand of security. Steganography is one of the techniques used for securing the data. The
secret message is hidden inside a cover media like audio, video or image with the help of a secret
key. Biometric templates can also be secured with this technique. Instead of storing original
templates in the database stego–image is stored. LSB is one of the common techniques that replace
the LSB of every pixel of the cover image with the secret message to form stego–image.
Keywords: Biometric, Biometric Attacks, Biometric template, Steganography, Security.
1. Introduction
With increasing rate of attacks, everyone today needs a reliable and secure system. Biometric
systems fulfil the needs to a great extent as biometric traits are better than passwords or pins which
have chances of being stolen and forgotten. Before using biometric systems enrolment phase is
necessary during which the templates of the users are stored in the database. During authentication
user 's claim is matched with the

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

Cognitive Signal Processing : Feature Estimation
Behavioural Signal Processing: Feature Estimation in Speech
Abstract
Human behaviour interrelates closely with the human beings' mental state. The behavioural
information reflects communication, social interaction and even personality. To build a bridge to the
human mind over engineering advances, an operational method, Behavioural Signal Processing
(BSP) technology, has been introduced, which aims to analyse speech–based human behaviour. The
main task of this project is the feature estimation based on BSP. In feature extraction, there are
numerous analysis modes, of which the Mel–frequency cepstral (MFC) represents the short–term
power spectrum of a speech signal. As MFC is about the power spectrum and requires Fourier
Transform, this ... Show more content on Helpwriting.net ...
[1]
Moreover, behavioural research for psychological estimations deeply depends on cautious
evaluation of numerous observational indications. [5] Both the observation theory and current
experimental results state that significant other's behaviour is relevant with plentiful factors
including age, gender, education background, cultural background, life experiences as well as recent
mental and physical health conditions such as stress, illness, or disability. [3] Also, the affection
extent between intimate relationships matters much about how people act or communicate/speak. In
this project, the audio data is extracted from a dialogue in drama to simulate a marital discussion.
Behavioural Signal Processing
According to the main reference, "Toward automating a human behavioural coding system for
married couples' interactions using speech acoustic features", in this project, the self–reports of
observable behaviours can be extremely untrustworthy to some extent. Additionally, many of
speaking recognition algorithms centres more on demonstrating objective human behaviour, for
instance, the exact words, that is to say, what words or sentences people exactly say to their
partners. [1] Consequently, the paper states that one of effective methods to analyse the audio data is
Behavioural Signal Processing

Speech Processing : Using Mel Frequency Cepstral...
Speaker reognition using Mel Frequency Cepstral Coefficients(MFCC)
Abstract Speech processing has emerged as one of the most important application area of digital
signal processing. Various fields for research in speech processing are speech recognition, speaker
recognition, speech analysis, speech synthesis, speech coding etc. The objective of automatic
speaker recognition is to extract, characterize the discriminant features and recognize the
information about speaker identity. In this paper we present a voice recognition system based on
Mel Frequency Cepstral Coefficients (MFCC) and vector Quantization (VQ). This technique has an
advantage that it creates fingerprint of human voice by exploiting human acoustic system and
cepstral analysis. MFCC is widely accepted as a baseline for voice recognition due to these unique
features.
KeywordsMFCC, Vector Quantization, Speaker recognition, Feature extraction, Fast Fourier
Transform
Introduction
Human speech is the most natural form of communication and conveys both meaning and identity.
The identity of a speaker can be determined from the information contained in the speech signal
through speaker identiﬁcation. Speaker identiﬁcation is concerned with identifying unknown
speakers from a database of speaker models previously enrolled in the system. Speaker (voice)
identification has varied applications ranging from opening doors to security systems.
Speech processing is widely divided into 5 different

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

IFDM Communication Systems
OFDM is a great technique to handle impairments of wireless communication channels such as
multipath propagation. Hence, OFDM is a practical candidate for future 4G wireless
communications techniques [1]–[4]. On the other hand, one of the major drawbacks of the OFDM
communication system is the drift in reference carrier. The offset present in received carrier will
lose orthogonality among the carriers. Hence, the CFO causes a reduction of desired signal
amplitude in the output decision variable and introduces ICI. Then it brings up an increase of BER.
The effect caused by CFO for OFDM system was analyzed in [7]–[9]. In [7] BER upper bound of
OFDM system is analyzed without ICI self–cancellation and BER of OFDM system is analyzed
using self–cancellation, but this method is less accurate. In [9], it is indicated that CFO should be
less than 2% of the bandwidth of the sub–channel to guarantee the signal to interference ratio to be
higher than 30 dB. A critically sampled OFDM system/OQAM system is also not robust to CFO [9],
even when optimal pulses are used as shaping filters. Thus, carrier frequency offset greatly degrades
system performance. Therefore, practical OFDM systems need the CFO to be compensated with
sufficient accuracy, and this has led to a whole lot of literature on CFO estimation algorithms. Most
of the existing CFO estimators for OFDM are based on periodically transmitted pilot symbols. Yet,
the pilot symbols transmission loses a significant bandwidth,

Annotated Bibliography On Color Barcode
II. LTERATURE REVIEW
1)Homayoun Bagherinia, Roberto Manduchi,had proposed the for University of California, Santa
Cruz"A novel approach for color barcode decoding using smartphones"
The use of colors increases the information storage capacities in barcodes. Increasing the number of
color stolen code information makes the decoding a challenging task due to the dependency of the
surface color on the illuminant spectrum, viewing parameters, printing device and material. The
decoding becomes more challenging if a mobile phone as a decoding device is used due to the
capture of image from different distances as well as angles. We present an iterative decoding
algorithm that decodes the colors of all barcode patches across the barcode by ... Show more content
on Helpwriting.net ...
5) Amin Motahari , Member, IEEE, and Malek Adjouadi , Member, IEEE had Praposed the work for
"Barcode Modulation Method for Data Transmission in Mobile Devices" In this study, a new
approach for data modulation in 2–D barcodes is introduced, and its performance is evaluated in
comparison to other standard method of barcode modulation. In this new approach, orthogonal
frequency–division multiplexing (OFDM) modulation is used together with differential phase shift
keying (DPSK) over adjacent frequency domain elements. A specific aim of this study is to establish
a system that is proven tolerant to camera movements, picture blur, and light leakage within
neighboring pixels of an LCD.
III. THE PROPOSED PICODE SYSTEM In this section, the proposed PiCode system is described
with an emphasis on the novel aspects of the image modulation and demodulation process. For the
modulation part the details of the modulation scheme will be presented to illustrate how PiCode
preserves the perceptual quality of the embedded image while minimizing the interference of the
latter incurred on the modulation waveform. For the modulation part, the algorithms for performing
discrete cosine transform, block division will be described.
A. Image modulation
The various steps in image modulation are
Input image and message
Convert RGB to YUV
Block contrast
Divided into inner and outer

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
2 Asso. Prof . D.Y. Patil College of Engg and Technology, Kolhapur, Maharashtra.
3 Asso. Prof . 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

Analysis Of Watermarked Images Using Steganography

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