international journal of distributed computing and technology vol 2 issue 1

IJDCT

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e-ISSN: 2455-7307

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International Journal of Distributed

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Focus and Scope of the Journal! Decentralized computing

! Distributed algorithmic mechanism design

! Distributed cache

! Distributed operating system

! Multiprocessor and multi-core architectures

! Synchronization protocols and concurrent programming

! Parallel programming

! Distributed sensor networks

! Pervasive computing

! Optical computing

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Dr. Mansaf Alam AlamDepartment of Computer Science,

Jamia Millia Islamia, New Delhi, India

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Professor Ravi Prakash ReddyDepartment of IT GNITS, Shaikpet, Hyderabad,

India

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Vidyanagar, Nellore (Andhra Pradesh), India

Dr. Tripty SinghAsst.Professor, Amrita School of Engg,

Bangalore, India

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Institute of Technology, India

Dr. R G JeyakumarProfessor, Amrita School of Engineering,

Coimbatore., India

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Perundurai, Erode Tamilnadu, India

Ziyan WuResearch Scientist, Vision Solutions and

Technologies, Siemens Corporate Research, Princeton, NJ

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,Salem, India

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Engineering and Technology, Jamshedpur, India

Mr. S SivakumarPeriyar University, Salem,

India

B M Alaudeen Asst.Professor, AVS College of Arts & Science

,Salem, India

K Abirami Amrita School Of Engineering, Coimbatore,

India

Kalyan Kumar JenaDept. of CSEA, IGIT, Sarang, Odisha,

India

Ch.Satyananda ReddyAssociate Professor in the Department of

Computer Science and Systems Engineering, College of Engineering, Andhra University,

Visakhapatnam.

Dr. Kiran SreeProfessor in the department of CSE at

NBKRIST, India

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Dear Readers,

We would like to present, with great pleasure, the inaugural volume of a new scholarly

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Distributed operating system, Multiprocessor and multi-core architectures, Synchronization protocols and

concurrent programming, Parallel programming Distributed sensor networks, Pervasive computing,

Optical computing.

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Engineering.

Puneet Mehrotra

Managing Director

1. CSPC: A New Approach for Edge Detection of Gray-Scale Images Kalyan Kumar Jena, Sarojananda Mishra, Sasmita Mishra 1

2. An Improved Approach for Edge Detection of Noisy Images Kalyan Kumar Jena, Sarojananda Mishra, Sasmita Mishra 7

3. Analysis of Fingerprint Image Enhancement by Different MethodsMayur S. Patil, Sandip S. Patil 14

4. Short Communication: Human Resource Management SystemKshitij Singh Raghav 23

5. Location Search with Mobile Images Using Spatial DataAnirudh Mathur 25

Contents

IJDCT (2016) 1–6 © JournalsPub 2016. All Rights Reserved Page 1

International Journal of Distributed Computing and Technology ISSN: 2455-7307 (online)

Vol. 2: Issue 1

www.journalspub.com

CSPC: A New Approach for Edge Detection of Gray-Scale

Images

Kalyan Kumar Jena*, Sarojananda Mishra, Sasmita Mishra

Department of CSEA, IGIT, Sarang, Odisha, India

Abstract

We can define an edge of an image as a set of connected pixels that creates boundaries of

several objects in an image. Generally, Edge detection is a process of segmenting an image

into regions of discontinuity. Edge detection takes a greater role in digital image processing

as well as practical aspects of our life. Edges of an image can be generated by implementing

several edge detector mechanisms. In this paper, anew edge detection mechanism that

computes edges of different images using the quantitative combination of Canny-Sobel-

Prewitt-Canny (C-S-P-C) edge detectors is presented. Here, the proposed methodology is

compared with Canny, Sobel and Prewitt edge detectors separately.

Keywords: Canny-Sobel-Prewitt (C-S-P-C) edge detectors, edge detection, digital image

processing

INTRODUCTION

Digital image processing refers to the use

of computer algorithm in order to perform

image processing on several digital

images.[1]

It is a very popular mechanism

that can be widely used for digital image

processes or operations like pattern

recognition, segmentation, feature

extraction, image morphology, etc. Edge

detection is a very popular and well

developed field in image processing.

Edges normally arise on the boundary

between two different regions or objects in

an image.[2–19]

Generally, Edge detection mechanism

allows the user to check those features of

any image in which there is a more or less

abrupt change in case of gray level or

texture that indicates the end of one region

or object in the image as well as the

beginning of another. It has a lot of real

time applications like finger print

recognition, study of anatomical structure,

face recognition, medical imaging,

computer guided surgery diagnosis, locate

object in satellite images, automatic traffic

controlling systems, etc.[20–25]

There are

many traditional operators such as Sobel

Operator, Prewitt Operator, LOG

Operator, Canny Operator and Robert

Operator which are used for edge detection

of images.[6]

Different methods can be used for edge

detection. But, maximum methods can be

grouped into either Gradient or

Laplacian.[2]

In case of Laplacian method,

it checks for zero crossings in the 2nd

derivative of the image specifically to find

edges. In Image Processing and Computer

Vision, Edges give valuable and very

important information towards human

image understanding. [7]

Now-a-days, edge detection has become

very serious challenge to the image

processing scientist and researchers. Due



Vol. 2: Issue 1

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An Improved Approach for Edge Detection of Noisy Images

Kalyan Kumar Jena*, Sarojananda Mishra, Sasmita Mishra Department of CSEA, IGIT, Sarang, Odisha, India

Abstract

Edge detection of images is a very serious challenge to the researchers till date. Several

techniques can be implemented to detect the edges of different images. But a single edge

detection methodology is not enough to perform very well in each and every possible image

context. In this paper, an innovative edge detection methodology is presented, that computes

the edges of different images using the combination of Bergholm–Rothwell–Sobel–Prewitt

edge detectors (BRSP). Here, the edge detection of images using B-R-S-P technique is

compared with each Operator individually.

Keywords: Bergholm–Rothwell–Sobel–Prewitt edge detectors, B-R-S-P technique, Edge

detection, image context

INTRODUCTION

Edges in context of image processing and

computer vision provide valuable

information towards human image

understanding. It probably most important

processing step in human picture

recognition system consists of edge

detection process naturally.[1]

Edge

detection has become serious challenge to

image processing scientist.

Edge detection algorithm is essentially a

process of detection of this discontinues in

an image.[2,3]

Since the abrupt change in

brightness level indicates edge, its

detection in binary or segmented image is

quite straight forward. There could be

various reasons, such as lighting

conditions, object geometry, type of

material surface texture, etc. as well as

their mutual interaction, for

discontinuities.

How does edge comes in an image? The

answer to this question probably, provides

the early clue for locating edge in an

image.

The variation of image feature, usually

brightness gives rise to edges. Objectively

the edges are representation of the

discontinuities of image intensity

function.[4]

However, the process of edge

localization is quite complex in case of

gray level or intensity image.

The nature of intensity variation points to

application of derivative operators for

detecting edges, application of derivative

operator on intensity image produce

another image, usually called gradient

image as it reveals the rate of intensity

variation.

The transition in intensity in Gray scale

image is relatively smooth in nature rather

than abrupt in case of segmented image or

binary image. The image is then made to

undergo thresholding and /or edge linking

in order to yield contours. There are many

ways to perform edge detection.[2]



Vol. 2: Issue 1

www.journalspub.com

Analysis of Fingerprint Image Enhancement by Different

Methods

Mayur S. Patil*, Sandip S. Patil Department of Computer Engineering, SSBT’s COET, Bambhori, Jalgaon, Maharashtra, India

Abstract

The fingerprint enhancement method using directional filter/Rotational filter is effective in

both dry fingerprint images and wet fingerprint images. It removes noise in between the ridge

and filling the white hole in the ridge. This leads to decrease the False Acceptance Rate

(FAR) and False Rejection Rate (FRR), in fingerprint minutiae extraction. In fingerprint

image enhancement, for the image matching there are used various filters likes Gabor filter,

FFT filter etc. By using these filters the noise is reduced and image is cleared. Then this

image is matched with stored image.

Keywords: false acceptance rate (FAR) and false rejection rate (FRR), directional median

filter (DMF), multi-resolution analysis.

BACKGROUND

The biometry or biometrics refers to the

automatic identification of an individual

by using certain physiological or

behavioral traits associated with the

person.

Fingerprints are fully formed at about

seven months of fetus development and

finger ridge configurations do not change

throughout the life of an individual except

due to accidents such as bruises and cuts

on the fingertips.

A fingerprint consists of ridges as well as

valleys. The outline of the ridges and

valleys is unique for every individual.

There are two most important methods of

fingerprint matching: global pattern

matching and local Features. The first

approach analyses ridge bifurcations and

endings, the second technique represents

additional macroscopic approach. The last

approach considers the stream of ridges in

conditions of, for example, arches, whorls

and loops.

ROTATIONAL

FILTER/DIRECTIONAL FILTER

Directional Filter is one of the

enhancement techniques which are

familiar in multi-resolution enhancement

method. [1]

The Multi-resolution analysis

has been proposed to remove noise from

fingerprint image by decomposing the

image into different frequency bands (or

sub-images). This allows compensating for

different noise components at different

scales: in particular, at higher levels (low

and intermediate frequency bands) the

rough ridge-valley flow is cleaned and

gaps are closed, whereas at the lower

levels (Higher frequencies) the finer

details are preserved. The enhanced image

bands are then recombined to obtain the

final image. Generally, in directional filter

bank, the fingerprint image is divided into

eight parts according to the orientation of

the ridge structure. The eight orientations

IJACS (2016) 23–24 © JournalsPub 2016. All Rights Reserved Page 23

International Journal of Distributed Computing and Technology ISSN: 2455-7307(online)

Vol. 2: Issue 1

www.journalspub.com

Short Communication: Human Resource Management System

Kshitij Singh Raghav Department of MCA, Guru Gobind Singh IP University, New Delhi, India

Every organization has numerous types of

resources like office equipments, finance,

raw material, etc. Human Resource (HR)

is one of these resources. It is the most

vital among all the resources of an

organization. So, HR functions are

common to all type of organizations.

These HR functions may include

recruitment, time management,

management of payroll, and many more.

In the scenario of handling thousands of

employees, their recruitment procedure,

their time scheduling and their salary slip

generation according to their packages,

and their working days may become

difficult to handle manually. Here comes

the need of a system which can help the

administration to do all the above said

jobs in an automated and efficient

manner. We call our proposed system as

Human Resource Management System

(HRMS), which is being developed for

the management of human of HR.

Source: Wikipedia

There is a huge amount of information which needs to be entered, stored, and searched

thereafter related to large number of employee of a particular organization. HRMS reduces

the work load of the administration department by automating all the related process

electronically. This HRMS not only automates the data entry for employee details such as

personal information, past experience details, skills, and so on, but also efficiently manage

the time/work relation for every employee and the work distribution methods generates the

payment cheques periodically and


International Journal of Distributed Computing and Technology ISSN: 2455-7307(online)

Vol. 2: Issue 1

www.journalspub.com

Location Search With Mobile Images Using Spatial Data

Anirudh Mathur* Indian Institute of Technology, New Delhi, India

Abstract

This paper describes a method to do location recognition based on images taken from mobile

devices. Its usefulness emerges out when we are in a foreign land and because of language

barrier we fail to collect relevant information regarding popular monuments or structures.

Now searching a matching image would mean comparing earth’s moon with billions of stars

in the entire galaxy. It is computationally very expensive to match with billions of images

from web. So we devise a hybrid image-keyword-spatial data mechanism for searching.

Keywords: image, mobile, searching

INTRODUCTION

Majority of search engines today use

keyword based image searches. Image

based techniques often returns unrelated

images that are not even near to the

searched images.

Though these techniques are inherently

fast and computationally less expensive,

but again these techniques become less

relevant when we are in foreign unknown

land.

Google has a collection of more than a

million web pages.

These pages have been indexed with text

that appears near images or are image

caption etc. Google images already contain

EXIF data.

EXIF format has standard tags for location

information.

As of 2014 many cameras and most

mobile phones have a built-in GPS

receiver that stores the location

information in the EXIF header when a

picture is taken. Some other cameras have

a separate GPS receiver that fits into the

flash connector or hot shoe.

OUR APPROCH:

We propose a hybrid approach that can

provide content-based image retrieval by

combining spatial based, image-based and

text-based search.

We leverage the fact that there will be

redundant landmark images on the web

and that a search in a subset of the web

will likely find a matching image

We first search a set of images obtained by

crawling a restricted domain.

The domain is selected based on the spatial

data obtained either by GPS data of users

and using the mobile image send by user

for expected application, for example

monuments-related sites for a particular

geographic location.

GPS data are to be used in identifying the

region and each region already has a

database of geographic locations. This

IJDCT

International Journal of

Jan - Jun 2016

e-ISSN: 2455-7307

www.journalspub.com

Mechanical Engineering

Chemical Engineering

Architecture

Applied Mechanics

5 more...

1 more...

2 more...2 more...

5 more...

Computer Science and Engineering

Nanotechnology« International Journal of Solid State Materials« International Journal of Optical Sciences

Physics

Civil Engineering

Electrical Engineering

Material Sciences and Engineering

Chemistry

5 more...4 more...

3 more...

Biotechnology

3 more...

Nursing « International Journal of Immunological Nursing« International Journal of Cardiovascular Nursing« International Journal of Neurological Nursing« International Journal of Orthopedic Nursing« International Journal of Oncological Nursing

5 more... 4 more...

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international journal of distributed computing and technology vol 2 issue 1

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