CHAPTER ONE
1.0 INTRODUCTION
Face
recognition system is an application for identifying someone from image or
videos. Face recognition is classified into three stages ie)Face
detection,Feature Extraction ,Face Recognition. Face detection method is a
difficult task in image analysis. Face detection is an application for
detecting object, analyzing the face, understanding the localization of the
face and face recognition.It is used in many application for new communication
interface, security etc.Face Detection is employed for detecting faces from
image or from videos. The main goal of face detection is to detect human faces
from different images or videos.The face detection algorithm converts the input
images from a camera to binary pattern and therefore the face location
candidates using the AdaBoost Algorithm. The proposed system explains regarding
the face detection based system on AdaBoost Algorithm . AdaBoost Algorithm
selects the best set of Haar features and implement in cascade to decrease the
detection time .The proposed System for face detection is intended by using
Verilog and ModelSim,and also implemented in FPGA.
Face Detection System is to detect the face from image
or videos. To detect the face from video or image is gigantic. In face
recognition system the face detection is the primary stage. Figure 1 shows the
various stages of face recognition system ie face detection, feature extraction
and recognition. Now Face Detection is in vital progress in the real world
Face recognition is a pattern recognition technique
and one of the most important biometrics; it is used in a broad spectrum of
applications. The accuracy is not a major problem that specifies the
performance of automatic face recognition system alone, the time factor is also
considered a major factor in real time environments. Recent architecture of the
computer system can be employed to solve the time problem, this architecture
represented by multi-core CPUs and many-core GPUs that provide the possibility
to perform various tasks by parallel processing. However, harnessing the
current advancements in computer architecture is not without difficulties.
Motivated by such challenge, this research proposes a Face Detection and
Recognition System (FDRS). In doing so, this research work provides the
architectural design, detailed design, and four variant implementations of the
FDRS.
1.1 BACKGROUND OF THE RESEARCH
Face
recognition has gained substantial attention over in past decades due to its
increasing demand in security applications like video surveillance and
biometric surveillance. Modern
facilities like hospitals, airports, banks and many more another organizations
are being equipped with security systems including face recognition
capability. Despite of current success,
there is still an ongoing research in this field to make facial recognition
system faster and accurate. The accuracy
of any face recognition system strongly depends on the face detection
system. The stronger the face detection
system the better the recognition system would be. A face detection system can successfully
detect human face from a given image containing face/faces and from live video
involving human presence. The main
methods used in these days for face detection are feature based and image
based. Feature based method separates
human features like skin color and facial features whereas image based method
used some face patterns and processed training images to distinguish between
face and non faces. Feature based method
has been chosen because it is faster than image based method and its’
implementation is far more simplified.
Face detection from an image is achieved through image processing. Locating the faces from images is not a
trivial task; because images not just contain human faces but also non-face
objects in clutter scenes. Moreover,
there are other issues in face recognition like lighting conditions, face
orientations and skin colors. Due to
these reasons, the accuracy of any face recognition system cannot be 100%.
Face recognition is one of the most important
biometrics methods. Despite the fact that there are more reliable biometric
recognition techniques such as fingerprint and iris recognition, these
techniques are intrusive and their success depends highly on user cooperation.
Therefore, face recognition seems to be the most universal, non-intrusive, and
accessible system. It is easy to use, can be used efficiently for mass
scanning, which is quite difficult, in case of other biometrics . Also it is
natural and socially accepted.
Moreover, technologies that require multiple
individuals to use the same equipment to capture their biological
characteristics probably expose the user to the transmission of germs and
impurities from other users. However, face recognition is completely
non-intrusive and does not carry any such health dangers.
Biometrics is a rapidly developing branch of
information technology. Biometric technologies are automated methods and means
for identification based on biological and behavioral characteristics of an
individual. There are several advantages of biometric technologies compared to
traditional identification methods. To take adequate measures against
increasing security risks in modern world, countries are considering these
advantages and are shifting to new generation identification systems based on
biometric technologies.
1.2 STATEMENT OF RESEARCH PROBLEM
Biometric
systems are becoming an important element (gateway) for information security
systems. Therefore biometric systems themselves have to satisfy high security
requirements. Unfortunately producers of biometric technologies do not always
consider security precautions. In publications regarding biometric
technologies, drawbacks and weaknesses of these technologies have been
discussed. Since biometrics form the technology basis for large scale and very
sensitive identification systems (e.g. passports, identification cards), the problem
of adequate evaluation of the security of biometric technologies is a current
issue.
Also, some other issues with face detection and
recognition system is on individual with identical face like identical twins
and others, in situation like this it is possible for the system to make
mistake or error in processing the person image so as to grant access to the
rightful user.
1.3 OBJECTIVES OF THE STUDY
The
objective of this project is to implement a face recognition system which first
detects the faces present in either single image frames; and then identifies
the particular person by comparing the detected face with image database or in
the both image frames.
In addition to the main objective of this research
work, the researcher also went far more to add other features to the new system
which are as fellow.
1. One of the objectives
of this system is to design a system that will help the organization maintain a
strong security in the work environment.
2. Highlight areas of
vulnerability in the new system
3. Develop a ridged and
secure database for the organization to enable them secure their sensitive data
and records.
1.4 SIGNIFICANCE OF THE STUDY
This study is primarily aimed at increasing efficiency
in security, this research work will help the users in maintaining data. This
system will reduce the rate of fraudulent activities as it can as well keep
track of registered users and grant them access upon face recognition
completion.
Also the knowledge that would be obtained from this
research will assist the management to grow, also this research work will also
be of help to the upcoming researcher in this field of study both with the
academic students on their study.
1.5 SCOPE OF THE STUDY
The
scope of this study covers only on face detection and recognition, accessing
previous records and making matched for the data, updating of records and
making delete.
1.6 LIMITATION OF THE STUDY
Many
limitations encountered, were in the process of gathering information for the
development of this project work to this extent. It was not an easy one, so many constraints
were encountered during the collection of data.
The limitation focuses of the following constraints;
i. FINANCIAL
CONTRAINTS: the cost of sourcing for information and data that are involved in
this work is high in the sense that we all know that information is money.
ii. TIME: A
lot of time was involved in writing and developing this work,
iii. Irregularities in power supply also dealt harshly
with the researcher.
1.7 DEFINITION OF TERMS
Analysis: Breaking a problem into successively
manageable parts for individual study.
Attribute: A data item that characterize an object
Data flow: Movement of data in a system from a point
of origin to specific destination indicated by a line and arrow
Data Security: Protection of data from loss,
disclosure, modification or destruction.
Design: Process of developing the technical and
operational specification of a candidate system for implements.
File: Collection of related records organized for a
particular purpose also called dataset.
Flow Chart: A graphical picture of the logical steps
and sequence involved in a procedure or a program.
Form: A physical carrier of data of information
Implementation: In system development-phase that
focuses on user training, site preparation and file conversion for installing a
candidate system.
Maintenance: Restoring to its original condition
Normalization: A process of replacing a given file
with its logical equivalent the object is to derive simple files with no
redundant elements.
Operation System: In database – machine based software
that facilitates the availability of information or reports through the DBMS.
Password: Identity authenticators a key that allow
access to a program system a procedure.
Record: A collection of aggregates or related items of
a data treated as a unit.
Source Code: A procedure or format that allow
enhancements on a software package.
System: A regular or orderly arrangements of
components or parts in a connected and interrelated series or whole a group of
components necessary to some operation.
System Design: Detailed concentration on the technical
and other specification that will make the new system operational.
1.8 ORGANIZATION OF
THE WORK
The project is organized in five chapters. With introduction already being explained in
chapter 1 and the whole idea of this research work presentation in chapter one,
like objective of the study, statement of the research area of coverage
limitation and definition of terms all this makes up the chapter one.
Chapter 2; this section deals with the review of
study, review of concept theories upon which this work is built on, the
potential issues in the any face recognition system in the form of difference
in the lighting conditions in which the same picture appears differently and
the variations in skin color and pose.
Chapter 3 talks about the software tools used in the
project mainly related to visual basic programming language. The methodology at which this research work
will be implemented.
In chapter 4 the system is implemented and presented
with its analysis. Functions of the system and the operation of the system is
also, in depth explained for reader understating and comprehension.The system
requirement is also detailed and the platform at which the system can run on.
Chapter 5 summaries the whole work done and make
possible recommendation and suggest other points to be included into the work
for future propose