ABSTRACT
Wouldn’t you love to replace password based
access control to avoid having to reset forgotten password and worry about the intergrity of your system? Wouldn’t you like to rest secure in comfort that your healthcare system does not merely on your social security number as proof of your identity for granting access to your medical records?
Because each of these questions is becoming more and more important, access to a reliable personal identification is becoming increasingly essential .Conventional method of identification based on possession of ID cards or exclusive knowledge like a social security number or a password are not all together reliable. ID cards can be lost forged or misplaced; passwords can be forgotten or compromised. But a face is undeniably connected to its owner. It cannot be borrowed stolen or easily forged
CHAPTER-1
INTRODUCTION
The information age is
quickly revolutionizing the way transactions are completed. Everyday actions
are increasingly being handled electronically, instead of with pencil and paper
or face to face. This growth in electronic transactions has resulted in a
greater demand for fast and accurate user identification and authentication.
Access codes for buildings, banks accounts and computer systems often use PIN's
for identification and security clearences.
Using the proper PIN gains
access, but the user of the PIN is not verified. When credit and ATM cards are
lost or stolen, an unauthorized user can often come up with the correct
personal codes. Despite warning, many people continue to choose easily guessed
PIN's and passwords: birthdays, phone
numbers and social security numbers. Recent
cases of identity theft have
hightened the nee for methods to prove that someone is truly who he/she claims
to be.
What are
biometrics?
A biometric is a unique,
measurable characteristic of a human being that can be used to automatically
recognize an individual or verify an individual’s identity. Biometrics can
measure both physiological and behavioral characteristics. Physiological
biometrics (based on measurements and data derived from direct measurement of a
part of the human body) include:
·
Finger-scan
·
Facial Recognition
·
Iris-scan
·
Retina-scan
·
Hand-scan
Behavioral biometrics (based on measurements
and data derived from an action) include:
·
Voice-scan
·
Signature-scan
·
Keystroke-scan
A “biometric system” refers to the integrated
hardware and software used to conduct biometric identification or verification.
CHAPTER-2
FACE
RECOGNITION
THE
FACE:
The face is an important
part of who you are and how people identify you. Except in the case of identical twins, the
face is arguably a person's most unique physical characteristics. While humans
have the innate ability to recognize and distinguish different faces for
millions of years , computers are just now catching up.
For face recognition there
are two types of comparisons .the first is verification. This is where the
system compares the given individual with who that individual says they are and
gives a yes or no decision. The second is identification. This is where the
system compares the given individual to all the
other individuals in the database and gives a ranked list of matches. All identification or authentication technologies operate using the following four stages:
other individuals in the database and gives a ranked list of matches. All identification or authentication technologies operate using the following four stages:
·
Capture: a physical or behavioral sample is
captured by the system during enrollment and also in identification or
verification process.
·
Extraction: unique data is extracted from the
sample and a template is created.
·
Comparison: the template is then compared with
a new sample.
·
Match/non match : the system decides if the
features extracted from the new sample are a match or a non match.
Face recognition
technology analyze the unique shape ,pattern and positioning of the facial
features. Face recognition is very complex technology and is largely software
based. This Biometric Methodology establishes the analysis framework with tailored algorithms for each type of
biometric device. Face recognition starts
with a picture, attempting to find a person in the image. This can be
accomplished using several methods including
movement, skin tones, or blurred human shapes. The face recognition system locates the head and finally the eyes
of the individual. A matrix is then
developed based on the characteristics of the individual’s face. The method of defining the matrix
varies according to the algorithm (the mathematical process used by the
computer to perform the comparison). This matrix is then compared to matrices
that are in a database and a similarity score is generated for each comparison.
Artificial intelligence is
used to simulate human interpretation of faces. In order to increase the
accuracy and adaptability , some kind of machine learning has to be
implemented.
IMPLEMENTATION
OF FACE RECOGNITION TECHNOLOGY
The implementation of face
recognition technology include the following four stages:
·
data
acquisition
·
input
processing
·
face
image classification and decision making
Data
acquisition:
The input can be recorded
video of the speaker or a still image. A
sample of 1 sec duration consists of a 25 frame video sequence. More than one
camera can be used to produce a 3D representation of the face and to protect
against the usage of photographs to gain unauthorized access.
Input
processing:
A pre-processing module
locates the eye position and takes care of the surrounding lighting condition
and colour variance. First the presence of faces or face in a scene must be
detected. Once the face is detected, it must be localized and normalization
process may be required to bring the dimensions of the live facial sample in
alignment with the one on the template.
Some facial recognition
approaches use the whole face while others concentrate on facial components
and/ or regions(such as lips, eyes etc). the appearance of the face can change
considerably during speech and due to facial expressions. In particular the
mouth is subjected to fundemental changes
APPLICATIONS
The natural use of face
recognition
technology is the replacement of PIN, physical tokens or both
needed in automatic authorization or identification schemes. Additional uses
are automation of human identification or role authentication in such cases
where assistance of another human needed in verifying the ID cards and its
beholder.
There
are numerous applications for face recognition technology:
Government
Use
1. Law Enforcement: Minimizing victim
trauma by narrowing mugshot searches, verifying identify for court records, and
comparing school surveillance camera images to known child molesters.
1. Security/Counterterrorism. Access
control, comparing surveillance images to known
terrorists.
2. Immigration: Rapid progression
through Customs.
Commercial
Use
1. Day Care: Verify identity of
individuals picking up the children.
2. Residential Security: Alert homeowners
of approaching personnel.
3. Voter verification: Where eligible
politicians are
required to verify their identity
during a voting process. this is intended to stop 'proxy' voting where the vote
may not go as expected.
4. Banking using ATM: The software is
able to quickly verify a customers face.
5. Physical access control of buildings
areas ,doors, cars or net access.
Other potential
applications include
ATM and check-cashing security. The software is able
to quickly verify a customer's face.
After a customer consents, the ATM or
check-cashing kiosk captures a digital image of him. The FaceIt software then
generates a faceprint of the photograph to protect customers against identity
theft and fraudulent transactions. By using the facial recognition software,
there's no need for a picture ID, bankcard or personal identification number
(PIN) to verify a customer's identity. This way business can prevent fraud from
occurring.
CONCLUSION
Face recognition
technologies have been associated generally with very costly top secure
applications. Today the core technologies have evolved and the cost of
equipments is going down dramatically
due to the intergration and the increasing
processing power.
Certain application of face recognition technology are
now cost effective, reliable and highly accurate. As a result there are no
technological or financial barriers for stepping from the pilot project to
widespread deployment.
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