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Page 1: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

1 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

Page 2: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

2 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

PROJECT ABSTRACTS FOR YOUR

EASY REFERENCE

IEEE PAPERS 2009, 2008, 2007 and so on…

Sahasra Technology Solutions

#107,AmeerEstate, SR Nagar,Hyderabad. 500 038

Ph-99 4 99 81 2 81

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Why SAHASRA – Promise for the Best

Page 3: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

3 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

IMAGE SEGMENTATION USING ITERATIVE

WATERSHEDING PLUS RIDGE DETECTION

This paper presents a novel segmentation algorithm for metallographic

images, especially those objects without regular boundaries and

homogeneous intensity. In metallographic quantification, the complex

microstructures make the conventional approaches hard to achieve a

satisfactory partition.

We formulate the segmentation procedure as a new framework of

iterative watershed region growing constrained by the ridge information.

The seeds are selected by an effective double-threshold approach, and

the ridges are superimposed as the highest waterlines in watershed

transform.

To tackle the over-segmentation problem, the blobs are merged

iteratively with the utilization of Bayes classification rule. Experimental

results show that the algorithm is effective in performing segmentation

without too much parameter tuning.

Page 4: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

4 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

HIERARCHICAL CONTOUR MATCHING FOR

DENTAL X-RAY RADIOGRAPHS Received 6 October 2006; received in revised form 9 April 2007; accepted 18 May 2007

The goal of forensic dentistry is to identify individuals based on their dental

characteristics. In this paper we present a new algorithm for human

identification from dental X-ray images. The algorithm is based on matching

teeth contours using hierarchical chamfer distance.

The algorithm applies a hierarchical contour matching algorithm using multi-

resolution representation of the teeth. Given a dental record, usually a

postmortem (PM) radiograph, first, the radiograph is segmented and a multi-

resolution representation is created for each PM tooth. Each tooth is matched

with the archived antemortem (AM) teeth, which have the same tooth number,

in the database using the hierarchical algorithm starting from the lowest

resolution level.

At each resolution level, the AM teeth are arranged in an ascending order

according to a matching distance and 50% of the AM teeth with the largest

distances are discarded and the remaining AM teeth are marked as possible

candidates and the matching process proceeds to the following (higher)

resolution level.

After matching all the teeth in the PM image, voting is used to obtain a list of

best matches for the PM query image based upon the matching results of the

individual teeth. Analysis of the time complexity of the proposed algorithm

prove that the hierarchical matching significantly reduces the search space

and consequently the retrieval time is reduced. The experimental results on a

database of 187 AM images show that the algorithm is robust for identifying

individuals based on their dental radiographs.

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5 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

RECONSTRUCTION OF UNDERWATER IMAGE

BY BISPECTRUM

Reconstruction of an underwater object from a sequence of images

distorted by moving water waves is a challenging task. A new approach is

presented in this paper.

We make use of the bispectrum technique to analyze the raw image

sequences and recover the phase information of the true object. We test

our approach on both simulated and real-world data, separately.

Results show that our algorithm is very promising. Such technique has

wide applications to areas such as ocean study and submarine

observation.

Index Terms— bispectrum, water wave, image, reconstruction,

distortion, refraction.

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6 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

AUTOMATIC RECOGNITION OF EXUDATIVE

MACULOPATHY USING FUZZY CMEANS

CLUSTERING AND NEURAL NETWORKS

Retinal exudates are typically manifested as spatially random

yellow/white patches of varying sizes and shapes.

They are a characteristic feature of retinal diseases such as diabetic

maculopathy. An automatic method for the detection of exudate regions is

introduced comprising image colour normalisation, enhancing the

contrast between the objects and background, segmenting the colour

retinal image into homogenous regions using Fuzzy C-Means clustering,

and classifying the regions into exudates and non exudates patches

using a neural network.

Experimental results indicate that we are able to achieve 92% sensitivity

and 82% specificity.

Page 7: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

7 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

International Conference on Computer Systems and Technologies -

CompSysTech’07

AN IMPROVING MODEL WATERMARKING

WITH IRIS BIOMETRIC CODE

The Paper justifies need to work with new technology for perfect safety in

specific area of the human deal (the business).

The Problem same important with new technology - internet, all

multimedia author's system, video watch of the system, audio production

and etc. .

In this directions will lay each leading security system and modern

password with electronic document and key system of the passage with

modern cryptographic system. We discuss one problem with

watermarks, used biometric code for perfect the algorithm of the

watermark to safety.

Key words: Biometric Watermark, Iris code, Biometric system,

videowatch system, watermark with discrete wavelet transformation l.

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8 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

CALL ADMISSION CONTROL OPTIMIZATION

IN WIMAX NETWORKS Worldwide interoperability for microwave access (WiMAX) is a promising technology for

lastmile Internet access, particularly in the areas where wired infrastructures are not

available. In a WiMAX network, call admission control (CAC) is deployed to effectively control

different traffic loads and prevent the network from being overloaded.

In this paper, we propose a framework of a 2-D CAC to accommodate various features of

WiMAX networks. Specifically, we decompose the 2-D uplink and downlink WiMAX CAC

problem into two independent 1-D CAC problems and formulate the 1-D CAC optimization, in

which the demands of service providers and subscribers are jointly taken into account. To

solve the optimization problem, we develop a utility- and fairness-constrained optimal

revenue policy, as well as its corresponding approximation algorithm.

THERE exist many regions in the world where wired infrastructures (i.e., T 1, DSL, cables,

etc.) are difficult to deploy for geographical or economic reasons. To provide broadband

wireless access to these regions, many researchers advocate worldwide interoperability for

microwave access (WiMAX), which is an IEEE 802.16 standardized wireless technology based

on an orthogonal frequency-division multiplexing (OFDM ) physical-layer architecture.

To support a variety of applications, IEEE 802.16 has defined four types of service:

1) unsolicited grant service (UGS);

2) real-time polling service (rtPS);

3) non-real-time polling service (nrtPS); and

4) best effort (BE) service.

In a WiMAX network with heterogeneous traffic loads, it is essential to find a call admission

control (CAC) solution that can effectively allocate bandwidth resources to different

applications. In this Project, a proposed WiMAX CAC framework, which effectively meets all

operational requirements of WiMAX networks. In this CAC framework, we decompose the 2-D

uplink (UL) and downlink (DL) WiMAX CAC problem into two independent 1-D CAC problems.

We further formulate the 1-D CAC as an optimization problem under a certain objective

function, which should be chosen to maximize either the revenue of service providers or the

satisfaction of subscribers.

With respect to 1-D CAC optimization problems, most previous studies were focused only on

two approaches:

1) the optimal revenue strategy (also known as the stochastic knapsack problem) and

2) the minimum weighted sum of blocking strategy .

In this project, we will show that these two strategies are, in fact, equivalent. Therefore, we

can mainly concentrate on the investigation of the optimal revenue strategy and view the

minimum weighted sum of blocking strategy as the basis for fast calculation algorithms.

Clearly, the optimal revenue policy only considers the profit of service providers. As an

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9 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

effort to conduct a multi objective study, in this paper, we will also take into account the

requirements from WiMAX subscribers and develop a policy with a satisfactory tradeoff

between service providers and subscribers.

The Project includes the following:

1) The development of a framework of CAC for WiMAX networks;

2) The investigation on various CAC optimization strategies; and

3) The proposal of a series of constrained greedy revenue algorithms for fast calculation.

Through detailed performance evaluation, the study carried out in this paper will show that

the proposed CAC solution can meet the expectations of both service providers and

subscribers.

Modules:

CAC model for WiMAX networks

Calculate the UL and DL capacity

1-D CAC optimization strategies and develop their corresponding approximation algorithms

The following parameters calculate using Greedy algorithm:

Utility Requirement

Fairness Requirement

Constrained Optimal Revenue Strategy

Simulation graphs:

Traffic arrival vs Revenue

Traffic arrival vs Utility

Blocking probability vs Traffic arrival

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10 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

ROBUST DWT-SVD DOMAIN IMAGE

WATERMARKING

Watermarking (data hiding) is the process of embedding data into a

multimedia element such as image, audio or video. This embedded data

can later be extracted from, or detected in, the multimedia for security

purposes. A watermarking algorithm consists of the watermark structure,

an embedding algorithm, and an extraction, or a detection, algorithm.

Watermarks can be embedded in the pixel domain or a transform

domain. In multimedia applications, embedded watermarks should be

invisible, robust, and have a high capacity. Invisibility refers to the

degree of distortion introduced by the watermark and its affect on the

viewers or listeners. Robustness is the resistance of an embedded

watermark against intentional attacks, and normal A/V processes such

as noise, filtering (blurring, sharpening, etc.), resampling, scaling,

rotation, cropping, and lossy compression.

Capacity is the amount of data that can be represented by an embedded

watermark. The approaches used in watermarking still images include

least-significant bit encoding, basic M-sequence, transform techniques,

and image-adaptive techniques.An important criterion for classifying

watermarking schemes isthe type of information needed by the detector:

• Non-blind schemes: Both the original image and the secret key(s) for

watermark embedding.

• Semi-blind schemes: The secret key(s) and the watermarkbit sequence.

• Blind schemes: Only the secret key(s).

Typical uses of watermarks include copyright protection (identification of

the origin of content, tracing illegally distributed copies) and disabling

unauthorized access to content. Requirements and characteristics for the

digital watermarks in these scenarios are different, in general.

Identification of the origin of content requires the embedding of a single

watermark into the content at the source of distribution.

To trace illegal copies, a unique watermark is needed based on the location

or identity of the recipient in the multimedia network. In both of these

applications, non-blind schemes are appropriate as watermark extraction or

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detection needs to take place in a special laboratory environment only when

there is a dispute regarding the ownership of content.

For access control, the watermark should be checked in every

authorized consumer device used to receive the content, thus requiring

semi-blind or blind schemes. Note that the cost of a watermarking

system will depend on the intended use, and may vary considerably.

Two widely used image compression standards are JPEG and JPEG2000.

The former is based on the Discrete Cosine Transform (DCT), and the

latter the Discrete Wavelet Transform (DWT).

In recent years, many watermarking schemes have been developed

using these popular transforms. Permission to make digital or hard

copies of all or part of this work for personal or classroom use is

granted without fee provided that copies are not made or distributed for

profit or commercial advantage and that copies bear this notice and the

full citation on the first page.

To copy otherwise, or republish, to post on servers or to redistribute to

lists, requires prior specific permission and/or a fee.In all frequency

domain watermarking schemes, there is a conflict between robustness

and transparency. If the watermark is embedded in perceptually most

significant components, the scheme would be robust to attacks but the

watermark may be difficult to hide.

On the other hand, if the watermark is embedded in perceptually

insignificant components, it would be easier to hide the watermark but

the scheme may be least resistant to attacks. In image watermarking,

two distinct approaches have been used to represent the watermark. In

the first approach, the watermark is generally represented as a sequence of

randomly generated real numbers having a normal distribution with zero

mean and unity variance.

This type of watermark allows the detector to statistically check the

presence or absence of the embedded watermark. In the second

approach, a picture representing a company logo or other copyright

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12 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

information is embedded in the cover image. The detector actually

reconstructs the watermark, and computes its visual quality using an

appropriate measure.

FILTERBANK-BASED FINGERPRINT MATCHING

With identity fraud in our society reaching unprecedented proportions and with an

increasing emphasis on the emerging automatic personal identification applications,

biometrics-based verification, especially fingerprint-based identification, is receiving a

lot of attention. There are two major shortcomings of the traditional approaches to

fingerprint representation.

For a considerable fraction of population, the representations based on explicit

detection of complete ridge structures in the fingerprint are difficult to extract

automatically. The widely used minutiae-based representation does not utilize a

significant component of the rich discriminatory information available in the

fingerprints. Local ridge structures cannot be completely characterized by minutiae.

Further, minutiae-based matching has difficulty in quickly matching two fingerprint

images containing different number of unregistered minutiae points. The proposed

filter-based algorithm uses a bank of Gabor filters to capture both local and global

details in a fingerprint as a compact fixed length FingerCode. The fingerprint

matching is based on the Euclidean distance between the two corresponding

FingerCodes and hence is extremely fast.

We are able to achieve a verification accuracy which is only marginally inferior to the

best results of minutiae-based algorithms published in the open literature. Our

system performs better than a state-of-the-art minutiae-based system when the

performance requirement of the application system does not demand a very low false

acceptance rate. Finally, we show that the matching performance can be improved by

combining the decisions of the matchers based on complementary (minutiae-based

and filter-based) fingerprint information.

Index Terms: Biometrics, FingerCode, fingerprints, flow pattern, Gabor filters, matching, texture, verification

Page 13: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

13 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

EIGENFACES FOR RECOGNITION Research on automatic face recognition in images has rapidly

developed into several inter-related lines, and this research has

both lead to and been driven by a disparate and expanding set of

commercial applications.

The large number of research activities is evident in the

growing number of scientific communications published on

subjects related to face processing and recognition.

Index Terms: face, recognition, eigenfaces, eigenvalues,

eigenvectors, Karhunen-Loeve algorithm.

Page 14: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

14 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

PROJECT ABSTRACTS FOR YOUR EASY

REFERENCE

IEEE PAPERS 2009, 2008, 2007 and so on…

Page 15: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

15 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

Page 16: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

16 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

SPEECH RECOGNITION SYSTEM

FOR ISOLATED WORDS

Speech recognition technology is used more and more for telephone

applications like travel booking and information, financial account

information, customer service call routing, and directory assistance.

Using constrained grammar recognition, such applications can achieve

remarkably high accuracy. Research and development in speech

recognition technology has continued to grow as the cost for

implementing such voice-activated systems has dropped and the

usefulness and efficacy of these systems has improved.

For example, recognition systems optimized for telephone applications

can often supply information about the confidence of a particular

recognition, and if the confidence is low , it can trigger the application to

prompt callers to confirm or repeat their request.

Furthermore, speech recognition has enabled the automation of certain

applications that are not automatable using push-button interactive

voice response (IVR) systems, like directory assistance and systems

that allow callers to "dial" by speaking names listed in an electronic

phone book.

Index Terms: speech, recognition, verification, sound, isolated, words.

IRIS RECOGNITION SYSTEM

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17 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

The iris of each eye is unique. No two irises are alike in their mathematical

detail--even between identical twins and triplets or between one's own left and

right eyes. Unlike the retina, however, it is clearly visible from a distance,

allowing easy image acquisition without intrusion.

The iris remains stable throughout one's lifetime, barring rare disease or

trauma. The random patterns of the iris are the equivalent of a complex

"human barcode," created by a tangled meshwork of connective tissue and

other visible features. The iris recognition process begins with video-based

image acquisition that locates the eye and iris.

The boundaries of the pupil and iris are defined, eyelid occlusion and specular

reflection are discounted, and quality of image is determined for processing.

The iris pattern is processed and encoded into a record (or "template"), which is

stored and used for recognition when a live iris is presented for

comparison. Half of the information in the record digitally describes the

features of the iris, the other half of the record controls the comparison,

eliminating specular reflection, eyelid droop, eyelashes, etc.

A biometric system provides automatic identification of an individual based

on a unique feature or characteristic possessed by the individual. Iris

recognition is regarded as the most reliable and accurate biometric

identification system available. Most commercial iris recognition systems use

patented algorithms developed by Daugman, and these algorithms are able to

produce perfect recognition rates. However, published results have usually

been produced under favourable conditions, and there have been no

independent trials of the technology.

The iris recognition system consists of an automatic segmentation system

that is based on the Hough transform, and is able to localise the circular iris

and pupil region, occluding eyelids and eyelashes, and reflections. The

extracted iris region was then normalised into a rectangular block with

constant dimensions to account for imaging inconsistencies.

Finally, the phase data from 1D Log-Gabor filters was extracted and

quantised to four levels to encode the unique pattern of the iris into a

bit-wise biometric template. The Hamming distance was employed for

classification of iris templates, and two templates were found to match if

a test of statistical independence was failed. The system performed with

perfect recognition on a set of 75 eye images; however, tests on another

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18 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

set of 624 images resulted in false accept and false reject rates of

0.005% and 0.238% respectively. Therefore, iris recognition is shown to

be a reliable and accurate biometric technology.

Index Terms: iris, recognition, verification, gabor, eye recognition,

matching, verification.

OPTICAL CHARACTER RECOGNITION Optical character recognition (OCR) is the translation of optically

scanned bitmaps of printed or written text characters into character

codes, such as ASCII. This is an efficient way to turn hard-copy

materials into data files that can be edited and otherwise manipulated on a

computer.

This is the technology long used by libraries and government agencies to

make lengthy documents quickly available electronically. Advances in OCR

technology have spurred its increasing use by enterprises. For many

document-input tasks, OCR is the most cost-effective and speedy method

available.

And each year, the technology frees acres of storage space once given

over to file cabinets and boxes full of paper documents. Before OCR can

be used, the source material must be scanned using an optical scanner

(and sometimes a specialized circuit board in the PC) to read in the page

as a bitmap (a pattern of dots). Software to recognize the images is also

required.

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19 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

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20 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

EIGENEXPRESSIONS FOR FACIAL

EXPRESSION RECOGNITION

We propose an algorithm for facial expression recognition which can

classify the given image into one of the seven basic facial expression

categories (happiness, sadness, fear, surprise, anger, disgust and

neutral).

PCA is used for dimensionality reduction in input data while retaining

those characteristics of the data set that contribute most to its variance,

by keeping lower-order principal components and ignoring higher-order

ones. Such low -order components contain the "most important" aspects of

the data.

The extracted feature vectors in the reduced space are used to train the

supervised Neural Network classifier. This approach results extremely

powerful because it does not require the detection of any reference point or

node grid.

The proposed method is fast and can be used for real-time applications.

JPEG-BASED IMAGE COMPRESSION

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21 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

TECHNOLOGY

JPEG is a standardized image compression mechanism. It stands for

Joint Photographic Experts Group, the original name of the committee

that wrote the standard. JPEG is designed for compressing either

fullcolor or gray-scale images of natural, real-world scenes.

It works well on photographs, naturalistic artwork, and similar material;

not so well on lettering, simple cartoons, or line drawings. JPEG is a

lossy compression algorithm, meaning that the decompressed image

isn't quite the same as the one you started with.

JPEG is designed to exploit known limitations of the human eye (more

about this later), notably the fact that small color changes are perceived

less accurately than small changes in brightness.

A useful property of JPEG is that the degree of lossiness can be varied

by adjusting compression parameters. This means that the image maker

can trade off file size against output image quality. The code we have

developed includes:

• Color space transformation between RGB and YCbCr •

Quantization

• Optimized encoding

OFF-LINE SIGNATURE RECOGNITION

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22 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

There exist a number of biometrics methods today e.g. Signatures,

Fingerprints, Iris etc. There is considerable interest in authentication

based on handwritten signature verification system as it is the cheapest

way to authenticate the person.

Fingerprints and Iris verification require the installation of costly

equipments and hence can not be used at day to day places like Banks

etc. As because Forensic experts can not be employed at every place,

there has been considerable effort towards developing algorithms that

could verify and authenticate the individual’s identity. Many times the

signatures are not even readable by human beings.

Therefore a signature is treated as an image carrying a certain pattern of

pixels that pertains to a specific individual. Signature Verification

Problem therefore is concerned with determining whether a particular

signature truly belongs to a person or not.

Signatures are a special case of handwriting in which special characters

and flourishes are viable. Signature Verification is a difficult pattern

recognition problem as because no two genuine signatures of a person

are precisely the same. Its difficulty also stems from the fact that skilled

forgeries follow the genuine pattern unlike fingerprints or irises where

fingerprints or irises from two different persons vary widely.

Ideally interpersonal variations should be much more than the

intrapersonal variations. Therefore it is very important to identify and

extract those features which minimize intrapersonal variation and

maximize interpersonal variations.

There are two approaches to signature verification, online and offline

differentiated by the way data is acquired. In offline case signature is

obtained on a piece of paper and later scanned. While in online case

signature is obtained on an electronic tablet and pen. Obviously

dynamic information like speed, pressure is lost in offline case unlike

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online case.

A DIGITAL IMAGE COPYRIGHT

PROTECTION SCHEME BASED ON VISUAL

CRYPTOGRAPHY A simple watermarking method for color images is proposed. The proposed method

is based on watermark embedding for the histograms of the HSV planes using visual

cryptography watermarking. The method has been proved to be robust for various

image processing operations such as filtering, compression, additive noise, and

various geometrical attacks such as rotation, scaling, cropping, flipping, and

shearing.

The watermark method is an excellent technique to protect the copyright ownership of

a digital image. The proposed watermark method is built up on the concept of

visual cryptography. According to the proposed method, the watermark pattern does

not have to be embedded into the original image directly, which makes it harder to

detect or recover from the marked image in an illegal way.

It can be retrieved from the marked image without making comparison with the

original image. The notary also can off-line adjudge the ownership of the suspect

image by this method. The watermark pattern can be any significant black/white

image that can be used to typify the owner.

Experimental results show that the watermark pattern in the marked image has good

transparency and robustness. By the proposed method, all the pixels of the marked

image are equal to the original image.

Index Terms: Matlab, source, code, histogram, HSV, visual, cryptography, watermark,

hue, saturation, value.

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HIGH DEFINITION IMAGE COMPRESSION

TECHNOLOGY The transport of images across communication paths is an expensive

process. Image compression provides an option for reducing the

number of bits in transmission. This in turn helps increase the volume of

data transferred in a space of time, along with reducing the cost

required. It has become increasingly important to most computer

networks, as the volume of data traffic has begun to exceed their

capacity for transmission.

Traditional techniques that have already been identified for data

compression include: Predictive coding, Transform coding and Vector

Quantization. In brief, predictive coding refers to the decorrelation of

similar neighbouring pixels within an image to remove redundancy.

Following the removal of redundant data, a more compressed image or

signal may be transmitted.

Transform-based compression techniques have also been commonly

employed. These techniques execute transformations on images to

produce a set of coefficients. A subset of coefficients is chosen that

allows good data representation (minimum distortion) while maintaining

an adequate amount of compression for transmission.

The results achieved with a transform-based technique is highly

dependent on the choice of transformation used (cosine, wavelet,

Karhunen-Loeve etc). Finally, vector quantization techniques require the

development of an appropriate codebook to compress data.

Usage of codebooks do not guarantee convergence and hence do not

necessarily deliver infallible decoding accuracy. Also the process may

be very slow for large codebooks as the process requires extensive

searches through the entire codebook. Following the review of some of

the traditional techniques for image compression, it is possible to

discuss some of the more recent techniques that may be employed for

data compression.

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25 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

FAST DCT VIA MOMENTS

Discrete cosine transforms (DCTs) are widely used in speech coding and

image compression. They resemble Karhunen- Loeve transform for first-

order Markov stationary random data and are classified into four groups.

Finding fast computational algorithms for DCTs has been a rather active

subject. These methods all tried to reduce the amount of multiplications.

It is very important to low -power implementations of DCTs on mobile

devices that no floating multiplications or less multiplications are

needed.

At the same time, the parallel hardware methods also have been

developed for designing fast DCT processors. Among them the systolic

array methods have been given more attentions due to their easy VLSI

implementation.

By using a modular mapping and truncating, DCTs are approximated by

linear sums of discrete moments computed fast only through additions.

This enables us to use computational techniques developed for

computing moments to compute DCTs efficiently. We demonstrate this

by applying our earlier systolic solution to this problem. The method can

also be applied to multidimensional DCTs as well as their inverses.

Index Terms: DCT, discrete cosine transform, moments, moment, fast

transform, systolic array, Matlab source code.

Page 26: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

26 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

FAST AND ROBUST SPEECH RECOGNITION

BASED ON DYNAMIC TIME-WARPING

Searching for the best path that matches two time-series signals is the

main task for many researchers, because of its importance in these

applications. Dynamic Time-Warping (DTW) is one of the prominent

techniques to accomplish this task, especially in speech recognition

systems. DTW is a cost minimisation matching technique, in which a test

signal is stretched or compressed according to a reference template.

Although there are other advanced techniques in speech recognition

such as the hidden Markov modelling (HMM) and artificial neural network

(ANN) techniques, the DTW is widely used in the small-scale embedded-

speech recognition systems such as those embedded in cell phones.

The reason for this is owing to the simplicity of the hardware

implementation of the DTW engine, which makes it suitable for many

mobile devices. Additionally, the training procedure in DTW is very

simple and fast, as compared with the HMM and ANN rivals.

Index Terms: Matlab, speech recognition, speech verification, speech

matching, Dynamic Time-Warping, dtw , features extraction.

Page 27: MATLAB Project Abstracts IEEE 2009 2010 Final Year Projects IEEE and Non IEEE Projects

27 | P a g e #107, AmeerEstate, Besides ICICI Bank, SR Nagar, Hyderabad. 500 038. Ph: 9949981281

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