ITC571 Assignment-2

(Project Proposal & Plan)

BIOMETRIC SYSTEMS

(Face Recognition)

Prepared by

AVINASH KANAPARTHI(11559587)

For the lecturer

ATHER SAEED

TABLE OF CONTENTS

RATIONALE..................................................................................................................................................................................1

DEFINING PROBLEM..........................................................................................................................................................1

PURPOSE AND JUSTIFICATION....................................................................................................................................3

RESEARCH QUESTIONS.........................................................................................................................................................4

PREVIOUS WORK......................................................................................................................................................................4

METHODOLOGY.........................................................................................................................................................................5

Research and System Development Method.......................................................................................................5

Data Collection Methods.................................................................................................................................................5

Ethical Issues......................................................................................................................................................................... 6

Requirement OF Compliance............................................................................................................................................6

Data Analysis......................................................................................................................................................................... 6

PROJECT PLAN........................................................................................................................................................................... 7

Deliverables........................................................................................................................................................................... 7

Work Breakdown Structure..........................................................................................................................................7

Risk analysis.......................................................................................................................................................................... 8

Duration................................................................................................................................................................................... 9

Gantt chart.............................................................................................................................................................................. 9

REFERENCES.............................................................................................................................................................................10

B I O M E T RI C S E C U RI T Y : F A C E RE C O G N I T I O N

RATIONALE

DEFINING PROBLEM

Biometric is the new technology that is being used mainly for authentication purpose by identify

the human being from their physical characteristics such as fingerprints, retina scan, face

recognition etc. Biometric security in the present world is being considered the best technique in

ensuring safety. Among all the different biometric methods human face recognition has gained a

lot of popularity in the past few years and is mainly used by many security agencies to identify

the individuals. The added advantage that is there associated with facial recognition is that in

facial recognition there is no need for the person to be in contact with the system as the image of

the person can be captured from a distance. In face recognition the various patterns of the face

are identified with the image of the face that is there in the database and then if the person is

identified (Achmad & Firdausy, 2012). Mostly this system was developed to provide security but

over the years face recognition is also been used in various other applications.

The issues that are associated with this technology are being discussed below:

Highly dependent over the surroundings: Face recognition process is highly dependent

on the surrounding of the user and in situation where the lighting is not proper it can

cause problems in recognizing the person. Even if the person is wearing a cap or is

wearing glasses the system can encounter certain drawbacks.

Privacy: Privacy is another area of concerns that is associated with facial recognition as

any person can use facial recognition software to capture the face of a person with his or

her knowledge and can then access personal information or other accounts of the person.

Dependent on positioning of the face: Face recognition is highly dependent on the

position of the face and only works properly when the user is fully facing the system or is

not more than 20 degree off from the system. Even the distance can be a concern in

situation where the person is too close to the system (Agrawal & Sharma, 2016).

Difference in the facial expression: Another issue that can affect the working of the

biometric face recognition system is that in situations where the facial expression of a

person are different from the previous instance. Even if the system is asked to predict the

expression of a person it can wrongly interpret the expression (Arca, Campadelli, &

Lanzarotti, 2006).

Adaptability: Adaptability is another issue that is associated with a biometric system as

biometric system may fail to adapt to the facial changes that a person is bound to have

over the years due to his age, illness or in situation of an injury.

Maintenance: Maintenance of the biometric face recognition system is another are of

concern as it can be a tough and a highly expensive task. Organizations may be able to

spend a lot of money to install a face recognition system but may lag in maintain the

system due to the amount of cost that is required for its maintenance.

Efficient Threat models: For facial recognition system the threat models should be well

considered as this system is used to provide security and there can be instances where this

system will attacked by intruders or other malicious parties (Chen, Liao, Lin, & Han,

2001).

High implementation cost: The cost that is levied over the implementation of face

recognition system is very high thus it can only be afforded by companies or

organizations that are big and have adequate resources.

PURPOSE AND JUSTIFICATION

Biometrics face recognition is an emerging technology which has gained a lot of popularity and

importance over the year in ensuring security and providing authorization only to the authorized

in using certain services. The purpose of this research is to gain complete knowledge over the

topic and deliver the best and adequate knowledge about the face recognition.

The reason for using this topic for research is that face recognition is considered to be the future

in providing security and personal identification. It is now being used in many applications like

Facebook where face recognition is used to tag people over the photographs. It is considered to

be the faster and most reliable method in authentication (Firdausy & Achmad, 2011).

RESEARCH QUESTIONS

The research questions that are associated with biometric face recognition technique are:

What is face recognition technology?

What are the areas of its application?

What are the limitations of this technology?

What are face recognition techniques?

PREVIOUS WORK

In this paper the author (Lin, 2000) have provided a framework explaining the face recognition

system and the various issues that are there associated with this new emerging technology. In the

recent years face recognition has fathered much attention in various fields and is being

implemented by various organizations. The areas that have benefitted most from this technology

are network security, content indexing and video compression as in this the people are the main

point of attraction. Face recognition not only makes it impossible for the intruders to gain access

of the user’s information but also provides user friendly interface. The author in this paper has

also discussed the various face recognition algorithms.

METHODOLOGY

RESEARCH AND SYSTEM DEVELOPMENT METHOD

The research and system development method that is deployed for the development of the

biometric face recognition is performance evaluation. This method is deployed as it is best

describes the face recognition system that deploy human verification and identification model.

The development model that is proposed for the face recognition system would implement pre-

processing, representation and identification module (Moon, Seo, & Pan, 2016). For the purpose

of identification of the development method literature review were done so that complete

information of the topic can be gathered. The literature review provides complete in depth

knowledge about the topic, its areas of use and the area of concerns that are there associated with

it.

DATA COLLECTION METHODS

The various data collection methods that are used in this research are:

Questionnaires: Questionnaires are set of questions that are prepared so that they can be

asked from researchers. The questionnaires are mailed to the researchers so that they can

answer the questions asked in the questionnaire later on. The questions that are asked

through the questionnaires are very simple and thus produce effective results.

Interviews: Interviews of the researchers are conducted to get instant answers and quick

results. Interviews will allow collecting the information very quickly and is very cost

effective method for gathering information (Frick, 2009).

Previous work: All the online generals, articles and books that have been written in this

regard are searched so that complete information regarding face recognition system can

be accumulated.

ETHICAL ISSUES

The ethical issues that are associated with the research on face recognition are described below:

Conflict of interest: Conflict of interest between the researchers can be an ethical issue

that is related with the research over facial recognition system.

Tampering the information: Another ethical issue that is there is related to the

information that is gathered and can be tampered or changed when written.

REQUIREMENT OF COMPLIANCE

The compliance requirements that are associated with this research work are:

The data that is collected should be from reliable resources and the integrity of the data

should be maintained.

The data gathered should be self-explanatory and accurate.

DATA ANALYSIS

The data analysis method that is used to analyze the information is qualitative data analysis

method. This method allows analyzing useful information from large sources of data. This

method is about interpretations and impressions made by key researchers in their work (Hock

Koh, Ranganath, & Venkatesh, 2002).

PROJECT PLAN

DELIVERABLES

The deliverable of the research is that to provide complete knowledge about the biometric face

recognition system. The various areas where it is useful and what are the risks and issues that are

associated with it.

WORK BREAKDOWN STRUCTURE

Task Name Duration Start Finish

Biometric: Face Recognition System 51 days Mon 29-08-16

Mon 07-11-16

Starting Phase 9 days Mon 29-08-16

Thu 08-09-16

Defining the problem 2 days Mon 29-08-16

Tue 30-08-16

Defining the need 2 days Wed 31-08-16

Thu 01-09-16

Identifying the technology 3 days Fri 02-09-16 Tue 06-09-16

Understanding the technology 2 days Wed 07-09-16

Thu 08-09-16

Requirements 14 days Fri 09-09-16 Wed 28-09-16

Understanding the objectives 3 days Fri 09-09-16 Tue 13-09-16

Identifying the various data collection techniques 2 days Wed 14-09-

16Thu 15-09-16

Selecting the data collection technique 1 day Fri 16-09-16 Fri 16-09-16

Collecting data 3 days Mon 19-09-16

Wed 21-09-16

Identifying the resources 2 days Thu 22-09-16 Fri 23-09-16

Finalising the resources 1 day Mon 26-09-16

Mon 26-09-16

Analyse the data collected 2 days Tue 27-09-16

Wed 28-09-16

Methodology 5 days Thu 29-09-16

Wed 05-10-16

Identifying the methodology 3 days Thu 29-09-16

Mon 03-10-16

Finalizing the methodology to be used 2 days Tue 04-10-16

Wed 05-10-16

Implementation 7 days Thu 06-10-16 Fri 14-10-16

Implementing the selected methodology 7 days Thu 06-10-16 Fri 14-10-16

Testing 9 days Mon 17-10-16

Thu 27-10-16

Comparing deliverables with objectives 3 days Mon 17-10-16

Wed 19-10-16

Perform tests 4 days Thu 20-10-16

Tue 25-10-16

Collect test results 2 days Wed 26-10-16

Thu 27-10-16

Maintenance 4 days Fri 28-10-16 Wed 02-11-16

Identifying new methods 2 days Fri 28-10-16 Mon 31-10-16

Implementing new methods 2 days Tue 01-11-16

Wed 02-11-16

Project ends 3 days Thu 03-11-16

Mon 07-11-16

Complete Documentation 3 days Thu 03-11-16

Mon 07-11-16

RISK ANALYSIS

Risk Description Level Mitigation Plan

Budget The estimated budget

may exceed.

Medium The budget should be flexible.

Deadline The project may exceed

the estimated time.

Medium The timeline schedule should be

flexible and extra resources

should be allotted if a task is

running more than the set time

(Hsieh & Chen, 2011).

Quality The facial recognition

system may not provide

desired outcomes.

Low First a prototype is needed to be

developed so that the system can

be tested.

DURATION

Total Time: 51 Days

Start Date: 29-08-2016

End Date: 07-11-2016

GANTT CHART

REFERENCES

Achmad, B. & Firdausy, K. (2012). Neural Network-based Face Pose Tracking for Interactive

Face Recognition System. International Journal On Advanced Science, Engineering And

Information Technology, 2(1), 105. http://dx.doi.org/10.18517/ijaseit.2.1.164

Agrawal, A. & Sharma, P. (2016). Pose Invarient Face Recognition System. International Journal

Of Engineering And Computer Science. http://dx.doi.org/10.18535/ijecs/v5i6.43

Arca, S., Campadelli, P., & Lanzarotti, R. (2006). A face recognition system based on

automatically determined facial fiducial points. Pattern Recognition, 39(3), 432-443.

http://dx.doi.org/10.1016/j.patcog.2005.06.015

Chen, L., Liao, H., Lin, J., & Han, C. (2001). Why recognition in a statistics-based face

recognition system should be based on the pure face portion: a probabilistic decision-based

proof. Pattern Recognition, 34(7), 1393-1403. http://dx.doi.org/10.1016/s0031-3203(00)00078-9

Firdausy, K. & Achmad, B. (2011). Automatic Frontal Face Pose Tracking for Face Recognition

System. International Journal On Advanced Science, Engineering And Information

Technology,1(4), 399. http://dx.doi.org/10.18517/ijaseit.1.4.1

Frick, K. (2009). Microcosting Quantity Data Collection Methods. Medical

Care, 47(Supplement), S76-S81. http://dx.doi.org/10.1097/mlr.0b013e31819bc064

Hock Koh, L., Ranganath, S., & Venkatesh, Y. (2002). An integrated automatic face detection

and recognition system. Pattern Recognition, 35(6), 1259-1273. http://dx.doi.org/10.1016/s0031-

3203(01)00117-0

Hsieh, C. & Chen, W. (2011). A Face Recognition System Based on ASM Facial

Components. AMM,58-60, 2314-2319. http://dx.doi.org/10.4028/www.scientific.net/amm.58-

60.2314

Lin, S. (2000). An Introduction to Face Recognition Technology. Informing Science Special

Issue On Multimedia Informing Technologies, 3(1). Retrieved from

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.100.8398&rep=rep1&type=pdf

Moon, H., Seo, C., & Pan, S. (2016). A face recognition system based on convolution neural

network using multiple distance face. Soft Comput. http://dx.doi.org/10.1007/s00500-016-2095-

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