Face Recognition

CONTENTS :-
 Introduction
 Biometrics
 Face Recognition
 Implementation
 How it works ?
 Advantages and Disadvantages
 Applications
 Conclusion
 References

INTRODUCTION :-
 Everyday actions are increasingly being handled
electronically, instead of pencil and paper or face
to face.
 This growth in electronic transactions results in
great 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 clearances.
 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.
 Face recognition technology may solve this problem
since a face is undeniably connected to its owner
except in the case of identical twins.

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:- This biometrics is based on
measurements and data derived from direct
measurement of a part of the human body.
 Behavioral biometrics:- this biometrics is based on
measurements and data derived from an action.

TYPES OF BIOMETRICS :-
PHYSIOLOGICAL
a. Finger-scan
b. Facial Recognition
c. Iris-scan
d. Retina-scan
e. Hand-scan
BEHAVIORAL
a. Voice-scan
b. Signature-scan
c. Keystroke-scan

 It requires no physical interaction on behalf of the
user.
 It is accurate and allows for high enrolment and
verification rates.
 It does not require an expert to interpret the
comparison result.
 It can use your existing hardware infrastructure,
existing cameras and image capture. Devices will work
with no problems.
 It is the only biometric that allow you to perform
passive identification in a one to many environments.

FACE RECOGNITION
 In Face recognition there are two types of comparisons:-
 VERIFICATION- The system compares the given
individual with who they say they are and gives a yes or
no decision.
 IDENTIFICATION- The system compares the given
individual to all the Other individuals in the database
and gives a ranked list of matches.

CONTD…
 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 Samples are a match
or a non match.

IMPLEMENTATION
The implementation of face recognition technology
includes the following four stages:
 Image acquisition
 Image processing
 Distinctive characteristic location
 Template creation
 Template matching

IMAGE ACQUISITION
 Facial-scan technology can acquire faces from almost
any static camera or video system that generates images
of sufficient quality and resolution.
 High-quality enrollment is essential to eventual
verification and identification enrollment images define
the facial characteristics to be used in all future
authentication events.

IMAGE PROCESSING
 Images are cropped such that the ovoid facial image
remains, and color images are normally converted to
black and white in order to facilitate initial comparisons
based on grayscale characteristics.
 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.

DISTINCTIVE CHARACTERISTIC LOCATION
 All facial-scan systems attempt to match visible facial
features in a fashion similar to the way people recognize
one another.
 The features most often utilized in facial-scan systems
are those least likely to change significantly over time:
upper ridges of the eye sockets, areas around the
cheekbones, sides of the mouth, nose shape, and the
position of major features relative to each other.

CONTD..
 Behavioural changes such as alteration of hairstyle,
changes in makeup, growing or shaving facial hair,
adding or removing eyeglasses are behaviours that
impact the ability of facial-scan systems to locate
distinctive features, facial-scan systems are not yet
developed to the point where they can overcome
such variables.

 Enrolment templates are normally created from
a multiplicity of processed facial images.
 These templates can vary in size from less than
100 bytes, generated through certain vendors
and to over 3K for templates.
 The 3K template is by far the largest among
technologies considered physiological
biometrics.
 Larger templates are normally associated with
behavioural biometrics.

TEMPLATE MATCHING
 It compares match templates against enrolment
templates.
 A series of images is acquired and scored against the
enrolment, so that a user attempting 1:1 verification
within a facial-scan system may have 10 to 20 match
attempts take place within 1 to 2 seconds.
 facial-scan is not as effective as finger-scan or iris-scan
in identifying a single individual from a large
database, a number of potential matches are generally
returned after large-scale facial-scan identification
searches.

HOW FACIAL RECOGNITION SYSTEM
WORKS
 Facial recognition software is based on the ability to
first recognize faces, which is a technological feat in
itself. If you look at the mirror, you can see that your
face has certain distinguishable landmarks. These are
the peaks and valleys that make up the different facial
features.
 VISIONICS defines these landmarks as nodal points.
There are about 80 nodal points on a human face.

CONTD..
Here are few nodal points that are measured by the
software.
 Distance between the eyes
 Width of the nose
 Depth of the eye socket
 Cheekbones
 Jaw line
 Chin

SOFTWARE
 Detection- When the system is attached to a video
surveillance system, the recognition software
searches the field of view of a video camera for
faces. If there is a face in the view, it is detected
within a fraction of a second. A multi-scale algorithm
is used to search for faces in low resolution. The
system switches to a high-resolution search only after
a head-like shape is detected.
 Alignment- Once a face is detected, the system
determines the head's position, size and pose. A face
needs to be turned at least 35 degrees toward the
camera for the system to register it.

 Normalization-The image of the head is scaled and
rotated so that it can be registered and mapped into an
appropriate size and pose. Normalization is performed
regardless of the head's location and distance from the
camera. Light does not impact the normalization
process.
 Representation-The system translates the facial data
into a unique code. This coding process allows for
easier comparison of the newly acquired facial data to
stored facial data.
 Matching- The newly acquired facial data is
compared to the stored data and (ideally) linked to at
least one stored facial representation.

 The system maps the face and creates a face
print, a unique numerical code for that face.
Once the system has stored a face print, it can
compare it to the thousands or millions of face
prints stored in a database.
 Each face print is stored as an 84-byte file.

ADVANTAGES AND DISADVANTAGES
Advantages:
 There are many benefits to face recognition systems such as
its convenience and Social acceptability. all you need is your
picture taken for it to work.
Face recognition is easy to use and in many cases it can be
performed without a Person even knowing.
Face recognition is also one of the most inexpensive
biometric in the market and Its price should continue to go
down.
Disadvantages:
 Face recognition systems can’t tell the difference between
identical twins.

APPLICATIONS
The natural use of face recognition technology is the
replacement of PIN.
Government Use:
Law Enforcement: Minimizing victim trauma verifying
Identify for court records, and comparing school
surveillance camera images to know child molesters.
Security/Counterterrorism: Access control, comparing
surveillance images to Know terrorist.
Immigration: Rapid progression through Customs.
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.

Commercial Use:
Residential Security: Alert homeowners of approaching
personnel.
Banking using ATM: The software is able to quickly
verify a customer’s face.
Physical access control of buildings areas, doors, cars or
net access.

CONCLUSION
 Factors such as environmental changes and mild changes
in appearance impact the technology to a greater degree
than many expect.
 For implementations where the biometric system must
verify and identify users reliably over time, facial scan
can be a very difficult, but not impossible, technology to
implement successfully.

REFERENCES
 Biometricgroup.com/wiley
 Wikipedia.org
 Google

Face Recognition

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