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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. Face recognition technology may solve this problem since a face
is undeniably connected to its owner expect in the case of identical twins. Its nontransferable. The system can then compare scans to records stored in a central or local database or even on a smart card.
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.
Why we choose face recognition over other biometric?
There are a number reasons to choose face recognition. This
includes the following
1. It requires no physical inetraction on behalf of the user.
2. It is accurate and allows for high enrolment and verification rates.
3. It does not require an expert to interpret the comparison result.
4. It can use your existing hardware infrastructure, existing camaras and
image capture devices will work with no problems.
5. It is the only biometric that allow you to perform passive identification in a one to many environment (eg: identifying a terrorist in a busy Airport
terminal.
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:
• capture: a physical or behavioural 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.
There are essentially two methods of capture. One is video
imaging and the other is thermal imaging. Video imaging is more common as
standard video cameras can be used. The precise position and the angle of the
head and the surrounding lighting conditions may affect the system
performance. The complete facial image is usually captured and a number of
points on the face can then be mapped, position of the eyes, mouth and the
nostrils as a example. More advanced technologies make 3-D map of the face
which multiplies the possible measurements that can be made. Thermal
imaging has better accuracy as it uses facial temperature variations caused by
vein structure as the distinguishing traits. As the heat pattern is emitted from
the face itself without source of external radiation these systems can capture
images despite the lighting condition, even in the dark. The drawback is high
cost. They are more expensive than standard video cameras.