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Current Trends in Signal Processing

Jan - April 2014

(CTSP)ISSN: 2321-4252

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Current Trends in Signal Processing

(ISSN: 2321– 4252)

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I take the privilege to present the hard copy compilation for the [Volume 4 Issue (1)] of Journal of

Current Trends in Signal Processing(CTSP). The intension of CTSP is to create an atmosphere that

stimulates creativeness, research and growth in the area of Signal Processing.

The development and growth of the mankind is the consequence of brilliant Research done by

eminent Scientists and Engineers in every field. CTSP provides an outlet for Research findings and

reviews in areas of Signal Processing found to be relevant for National and International recent

developments & research initiatives.

The aim and scope of the Journal is to provide an academic medium and an important reference for

the advancement and dissemination of Research results that support high level learning, teaching and

research in the domain of Signal Processing.

Finally, I express my sincere gratitude to the Editorial board members for their continuous support to

bring this issue to its present form. Undoubtedly we could not release this issue without the amazing

efforts of our Editors/Reviewers and Advisory board members.

I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra

Director

STM Journals

Director's Desk

STM JOURNALS

1. Comparative Study of Future Processor Design Models for Energy Efficiency D.H. Ahir, Nikesh A. Shah 1

2. Devanagari Script Recognition System using Combined Approach Bamb Kalpesh. K, Zope R.G, Sharma K. S 4

3. Estimation Techniques in Image Restoration - A Survey Approach Swati Singhal, Vandana V. Thakare 11

4. Jitter Estimation in Voice Taru Aggarwal, Sharda Vashisth 17

5. Mobility Assistant for Disabled Person Ohm P. Jodhani, Darshan K. Patel, Milan D. Mungara,Viraj K. Gandhi, Ashish M. Kothari 21

6. Multi-Layer Perceptron Neural Network Based Person Identification Using Appearance Based Facial Feature Md. Rabiul Islam, Rizoan Toufiq 26

ContentsCurrent Trends in Signal Processing

CTSP (2014© STM Journals 2014. All Rights Reserved

Current Trends in Signal Processing ISSN: 2321-4252

Volume 4, Issue 1

www.stmjournals.com

Comparative Study of Future Processor Design Models

for Energy Efficiency

D.H. Ahir1, Nikesh A. Shah

2*

1Government Polytechnic, Rajkot, Gujarat, India

2Department of Electronics, Saurashtra University, Rajkot, Gujarat, India

Abstract This paper describes the comparative analysis of the conceived future many core processor models not only for optimum performance but having the efficient power

consumption too. There is a need of the energy efficient parallel cores along with the

high throughput and higher performance sequential core to have future competent processors to meet the demand of the Moore’s law. One can have homogeneous cores

structure as well as heterogeneous cores structure of the processors. The emphasis in this

paper is on identifying the processor structure type which is best suited to the future low power requirement. The conclusion of this research paper is to go for heterogeneous

structure having one more powerful processor core with many small energy efficient cores to get overall energy efficient processor.

Keywords: Core processor, power consumption, energy efficient, efficient processor

CTSP (2014)© STM Journals 2014. All Rights Reserved

Current Trends in Signal Processing ISSN: 2321-4252

Volume 4, Issue 1

www.stmjournals.com

Devanagari Script Recognition System using

Combined Approach

Bamb Kalpesh. K*, Zope R.G, Sharma K. S Department of Electronics and Telecommunication, SRES’ College of Engineering, Kopargaon, India

Abstract We envisioned serving simple technique with novel idea for the newcomers, working in the Devnagari Optical Character Recognition (DOCR) area. In this system, template

matching technique and statistical technique is combinely used for the character

recognition. Statistical information is considered as a feature of an image and here pixels

values are considered as feature to achieve the recognition. The numbers of comparisons

are drastically reduced compared to traditional template matching technique hence

performance of the system is improved. The correlation and related methods are used to find images that are similar to a template. The results are compared with results of

template matching technique in terms of elapsed time that is time required to recognize the character here. The recognized devanagari characters then translated in to English

through Google translator using Matlab which will provide human assistance in different

applications. In English OCR results were of such type that’s it can produce technology driven applications. The algorithm used is very effective and can serve as a basis for

further research towards other similar Indian scripts.

Keywords: Correlation, devanagari optical character recognition, segmentation,

statistical technique, template matching

CTSP (2014) © STM Journals 2014. All Rights Reserved

Current Trends in Signal Processing ISSN: 2321-4252

Volume 4, Issue 1

www.stmjournals.com

Estimation Techniques in Image Restoration - A Survey

Approach

Swati Singhal*, Vandana V. Thakare Department.of Electronics and Communication Engineering, Madhav Institute of Technology and

Science, Gwalior, India

Abstract In the present paper a comparative study of various estimation techniques based on neural network, MATLAB, partial differential equation (PDE) and other proposed

models for image restoration are been discussed. An image may be distorted, noisy or

blurred and not suitable for extracting desired information or data, so it needs to be restored for desired application. Image restoration techniques are oriented towards

modeling the degradation, blur and noise and applying an inverse procedure to

reconstruct the original scene. Some techniques require prior estimation of degradation causes and some are based on neural network based training set. For the dependence on

various factors and procedures, these techniques require a comparative evaluation.

Keywords: Image restoration, image deblurring, MATLAB, hough transform, markov

random field(MRF), multi-valued neuron(MVN), modified hopfield neural

network(MHNN), LAB & RBF neural network, PSNR(peak signal to noise ratio)

CTSP (2014)© STM Journals 2014. All Rights Reserved

Current Trends in Signal Processing ISSN: 2321-4252

Volume 4, Issue 1

www.stmjournals.com

Jitter Estimation in Voice

Taru Aggarwal*, Sharda Vashisth Department of Electrical, Electronics and Communication Engineering, ITM University,

Gurgaon, India

Abstract Jitter is present in brisk perturbations of the vocal cycle lengths and when they are

sampled at least at the rate of fundamental frequency they can be observed from one

cycle to the next .Voice quality estimation can be done by analyzing jitter since it provides a high association with voice disorders. It also explains the variance of pitch

keeps in the allowance of just noticeable difference, which can be attributed to the effect of audible feedback, and it affects the variance of jitter further. This is explained using a

mathematical model. The pitch changes with the jitter, and the jitter’s change is limited

by the pitch. Jitter is measured using very famous peak detection algorithm which estimates the absolute value of jitter. The jitter in percent defines the relative variance of

periods in a voiced speech sound. Pitch is explored to establish its relation with jitter.

Keywords: Jitter, pratt, matlab, pitch

CTSP (2014)© STM Journals 2014. All Rights Reserved

Current Trends in Signal Processing ISSN: 2321-4252

Volume 4, Issue 1

www.stmjournals.com

Mobility Assistant for Disabled Person

Ohm P. Jodhani, Darshan K. Patel*, Milan D. Mungara,

Viraj K. Gandhi, Ashish M. Kothari

Department of Electronics and Communication, Atmiya Institute of Technology

& Science, Rajkot, India

Abstract A development of an assistance system on a wheelchair for the physically challenged and

handicapped people to compensate their needs of manoeuvrability. This Mobility

Assistant accepts the input from the user and accordingly sends command to the wheelchair to traverse around the surrounding. The proposed system will sense the body

movement of a person sitting on a wheelchair and then shifts the wheelchair suitably so

that it moves towards the desired direction. Further the system can also be upgraded so

that it can detect object and obstacle on the way and thus helps it by adding more

safety.The system will be self-contained within the wheelchair so that it ensures maximum mobility.

Keywords: Camera module, matlab, image processing, arduino uno

CTSP (2014) © STM Journals 2014. All Rights Reserved

Current Trends in Signal Processing ISSN: 2321-4252

Volume 4, Issue 1

www.stmjournals.com

Multi-Layer Perceptron Neural Network Based Person

Identification Using Appearance Based Facial Feature

Md. Rabiul Islam*, Rizoan Toufiq Department of CSE, RUET, Rajshahi, Bangladesh

Abstract This paper deals with secure person identification system using Back-Propagation

learning neural network algorithm where appearance based facial feature and Principal

Component Analysis based dimensionality reduction technique have been used. To extract the appearance based facial features, Viola-Jones method has used as a face

detector, Stam’s method of Active Shape Model has applied for detecting the facial edges

and image pre-processing method has used for eliminating the background noises. For reducing the effect of uneven lighting from the facial images, contrast based edge

detector has been used for this work. Principal Component Analysis based reduced facial feature vector are feed to Back-Propagation learning neural network algorithm to create

the learned template which is finally used to classify the unknown facial pattern. To

measure the performance of the proposed system, extended Yale Face Database has been used which focuses the superiority of the proposed appearance based facial feature for

person identification system.

Keywords: Person identification, appearance based facial feature, principal

component analysis, back-propagation learning neural network.