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Abstract: -A technique of online face authentication has

been proposed which may be used for the user

identification. Pre processing of acquired image has been

accomplished through consecutive steps viz. image

reading and subsequent adjustment of illumination level

and feature extraction from a certain portion of the

clipped image to form a template. Provision for automatic

uploading of the template through internet to remote

server by the client background service has been made.

Eigen values of the clipped block of image, i.e. template

have been calculated and compared with those of alreadysaved image in the remote server in order to authenticate

the received image along with the password of the user.

The present work based on person based authentication

is expected to be less prone to be cracked by the hackers

and has provided a higher recognition rate of the

transmitted images from the client side.

Keywords - Face recognition system, online, SQL

server, ASP, User Identification.

I. INTRODUCTION

Authentication is a significant issue in system control

in computer based communication. Traditional accountbased authentication does not guarantee the identity of

the exact person of the account. This process has the

drawback that it is prone to be easily guessed by an

undesired person. One efficient way of overcome this

problem is to identify the person willing to access on

the basis of face based account. Human facerecognition is an important branch of biometric

verification and has been widely used in many

applications, such as video monitor system, human-

computer interaction, and door control system and

network security. The stand-alone version of face

based system has some application limitations. This

paper presents a design and realization of the online

face based identifying system. Whole system iscontrolled automatically uploads the local face image

to the

back ground face information will be

verified by MatLab code. After client pre-

processing, the client background service

remote server, then, the server background service

starts the recognition task and sends the recognition

result back to the client.

With the development of computer networking

systems, demand of automatic face recognition

system has been increasing rapidly for various

applications such as security and identification, and it

has become an active research area in bio-

informatics. Various methods of online face

recognition [1-3] have been proposed and applied inthe network security [4-6] and the criminal face

image retrieval [7].

Quanbin Li et al. [1] described and validated an

implementation scheme of online face recognition

system. They have used self database and ASP as

front end with illumination compensation, SMQT,

Delphi Algorithm. Hwangjun Song et al. [2] has

presented an online face recognition system through

the Internet. One unique feature has been proposed

by them and the system was based on multiple

frames while other face algorithms use only anoriginal image. Guo-Dong Guo et al [4] has proposed

the AdaBoost algorithm for face recognition. But nostudy on Online Face Authentication based on face

recognition and user identification is not available in

published literature.

An online face recognition system proposed by the

present authors consists of a server and network-

connected clients. The online face recognition system

can be defined as follows. It is a system pre-

processed input face images of the client are

automatically uploaded to the remote server through

the Internet by client background service. Then, the

server background service starts the recognition

process and sends the recognition result back to the

client using certain dynamic web page technology(e.g. ASP). It includes four main aspects viz. face

images acquisition and pre-processing of the data

collected from client; high-speed and reliable

transmission system through the Internet.

Capture

(Preprocessing) Compare Make Decision

Fig. 1: The Biometric Process steps proposed in the present work.

A Proposed Technique of Online Face Authentication to

Be Used For the User IdentificationDibyendu Ghoshal

Electronics and Instrumentation Engineering Department

National Institute of Technology, Agartala, IndiaE-mail: dghoshal_diet@rediffmail.com

9781457715839/ 12/ $26.00 2012

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Face Detection

We have proposed the Face Based Authentication

System (FBAS). FBAS conducts the authentication

depends on both face image and password. FBAS has

several advantages. First, the account factors of

account based authentication are replaced by face

images. Hence, the identity of the accessing person is

expected to become more secured. Secondly, in the

proposed method, only the face images are not enough

to login, the passwords will also be needed. Thirdly,

the owner of account can be identified by some other

means, but the face images cannot be easily fabricated.

Finally, it has been established

NoFigure 2: Proposed System Ove

that, the password can be utilized to enhance the

authentication rate.

II. SYSTEM OVERVIEW

Fig. 2 represents the system overview of the

proposed scheme of research. It is observed from the

scheme that when a user will sign up to the systemfor the first time, his face will be captured by the

camera which will be processed by Matlab codes in

the background. In case, Matlab codes are able to

recognise a human face, it will extract the region of

face and store it to the face database

Fig 2: Proposed System Overview.

Fig 3: The structure of the proposed online face recognition system.

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as its login identifier along with the password of the

person willing to access. Next time, when the same

user would try to login the system, his face would be

utilised by the server as his login identity. During this

process, his face will be captured and this will be sent

to the server. Then the server would compare the

existing face images already stored in the database

with that of the accessing user and at the same timeusers password would be tried to be matched by the

server. If it is found to be matched with existing

records of the database, the user will be permitted to

login.

III. SYSTEM DESIGN

Fig. 3 shows that the proposed system is fully based on

client server architecture. Client captures several

images, detects the face area of the images, resize and

compress the images if situation demands, and

transmits the resultant image thus obtained through the

Internet. The recognition process is done at server, and

extracted face image is stored in the servers databasefor future reference, and then it sends back the

recognition result to the client.

A. Face Information Databases Design

TABLE 1: IT IS THE TABLE SHOWING THE COMBINATIONOF USER ID AND PASSWORDS.

Face information database on the remote server

mainly contains information as shown in Table 1.

B. Client Design Process

In order to improve transmission efficiency and the

correct recognition rate, the pre-processing comprisesthree steps: first, read the image and subsequent

adjustment of the illumination on the image. Secondly,

the face region would be undergone detection process

and a follow-up clipping operation. Thirdly, the

clipped block of the image thus obtained would be

temporarily stored in the server for any future use.

After pre-processing, Eigen values of the clipped block

of the image will be calculated and compared with the

Eigen values of already saved face images in thedatabase.

In the present study, the background service on the

client/ server are developed based on Delphi

algorithm [11] the execution process of the client

service is given below

// the execution process of the client service

//start service through browser in client side

Detect and start capturing images through web

camera of the client side:

Begin

//Pre-process the captured image and extract face

image

//calculate the eigen value of the captured face

image and compared with eigen values of existing

faces in the database.

//If eigen value does not matched with existing

ones, upload the new face image to remote server

end;

C. Face Authentication on the Server

The PCA (Principal Component Analysis) method

for completing authentication process in the server

has been used in the present work.

C.1: PCA (Principal Component Analysis)

PCA method has been widely used in applications

such as face recognition and image compression.

PCA is a common technique for finding patterns indata, and expressing the data as eigenvector to

highlight the similarities and differences between

different data. The following steps summarize the

PCA process.

1. Let {D1,D2,DM} be the training data set. The

averageAvg is defined by:

2. Each element in the training data set differs from

Avg by the vector Yi=Di-Avg. The covariance matrix

Cov is obtained as:

3. Choose M significant eigenvectors of Cov as

EKs, and compute the weight vectors Wik for each

element in the training data set, where k varies from

1 to M.

Sl. no 1 2

User id

Password 1234 3456

Flags True True

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Using PCA algorithm the following authentication

steps would be followed in the server:

Begin:

// start service through browser in client side.

Detect and start capturing images through web camera

of the client side for login to the system// Pre-process the captured image and extract face

image and calculate the eigen value of the captured

face image and compared with eigen values of existing

faces in the database

// If eigen value does not match with existing ones,

login is failed.

// If eigen value is matched then the system will

check the corresponding password of the user, as the

combination of the user id and password are found

matched then login successfully done otherwise login

would failed.

end;

IV. EXPERIMENT

Experiments have been carried out by the present

authors with the help of the 100 face images collectedfrom the data base provided by the client side. Some

sample face images from the database are shown in

Fig. 4.

Fig. 4: Sample Faces stored in server.

The acquired new images from the client side would be

pre-processed on the client side itself, and the pre-

processing result has been shown in Fig. 5

(a) (b) (c)

Fig. 5: Pre-processing method

(a) original image

(b) marked portion of face region

(c) segment of face

region.

The screenshot of the client side as obtained by the

present method has been shown in Fig. 6. In this

method, the password of the user has been integrated

with the image of the users face to improve the

Fig 6: The screenshot of the Client Side.

recognition rate i.e. to obtain a higher ratio of image

recognition with the total number of the images input

to the system. The acquired face images by the

camera on the client side, and then the individual

password have been sent simultaneously as inputdata to be transmitted through the channel and

ultimately to be processed by the server background

services. If combination of face and password

matches with the data already stored in the server,

then the user is permitted to login the system. The

integration between the recognised image and the

user password takes place at the final stage of login.

The integration process has become obvious from

Fig. 6.

TABLE 2: FACE RECOGNITION RATE (UNDERBALANCED ILLUMINATION, WHITE BACKGROUND ANDFIXED DISTANCE BETWEEN CAMERA AND USER)

Face Orientation Recognition rate

00 98.7 %

18 80.0 %

54 19.2 %

> 700 0 %

Table 2 has shown the variation of the face

recognition rate with respect to the orientation of the

faces. It has been seen that the recognition rate of the

face is maximum when the direction of the face is

perpendicular to the image acquisition system e.g. a

camera.

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V. CONCLUTION

A novel technique has been proposed to authenticate

an user willing to login an account on the basis of

image of the user as well as the password. The

technique has focussed on person based authentication

and has been found to have several advantages. The

factors of account based authentication are replaced by

face images. Hence, the genuine person will only be

allowed to login. In the proposed method only the face

images are not enough to login, the passwords are still

needed. Thus, the system cannot be easily cracked by

simply presenting or inserting a picture of the user in

front of camera. Further it has been shown that the

password is able to be utilized to enhance the

recognition rate significantly.

ACKNOWLEDGMENT

The authors gratefully acknowledge the kind

inspiration provided by the Prof. Dr. P K Bose,

Director National Institute of Technology, Agartala.

DEDICATION

The research work is dedicated to the everlasting

memory of late Ms. Sumita Ghoshal, the only sister of

D. Ghoshal, who herself was a gem of scholar with

unfathomable knowledge and wisdom, beauty and

simplicity.

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