SEMINAR topic "Face Recognition Technology"
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bhaskarnani
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#1
03-01-2010, 12:07 PM


PLS give me more details about 'Face Recognition Technology' seminar and presentation paper...
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03-01-2010, 01:03 PM

please read topicideashow-to-face-recognition-technology-seminar and presentation-report for Face Recognition Technology' seminar and presentation paper. and report and more
Use Search at http://topicideas.net/search.php wisely To Get Information About Project Topic and Seminar ideas with report/source code along pdf and ppt presenaion
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#3
17-08-2012, 02:57 PM

Face Recognition Technology


.pdf   FACE_RECOGNITION_TECHNOLOGY.pdf (Size: 225.38 KB / Downloads: 24)

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

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.

CAPTURING OF IMAGE BY STANDARD VIDEO
CAMERAS


The image is optical in characteristics and may be thought of as a
collection of a large number of bright and dark areas representing the picture
details. At an instant there will be large number of picture details existing
simultaneously each representing the level of brightness of the scene to be
reproduced. In other words the picture information is a function of two
variables: time and space. Therefore it would require infinite number of
channels to transmit optical information corresponding to picture elements
simultaneously. There are practical difficulty in transmitting all information
simultaneously so we use a method called scanning.
Here the conversion of optical information to electrical form and
its transmission is carried out element by element one at a time in a sequential
manner to cover the entire image. A TV camera converts optical information
into electrical information, the amplitude of which varies in accordance with
variation of brightness.
An optical image of the scene to be transmitted is focused by lense
assembly on the rectangular glass plate of the camera tube. The inner side of
this has a transparent coating on which is laid a very thin layer of
photoconductive material. The photolayer has very high resistance when no
light is falling on it but decreases depending on the intensity of light falling on
it. An electron beam is formed by an electron gun in the TV camera tube. This
beam is used to pick up the picture information now avilable on the target plate
of varying resistace at each point.

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 but is also very important source for discriminating faces. So an approach to
persons recognition is developed based on spatio-temporal modeling of
features extracted from talking face. Models are trained specific to a persons
speech articulate and the way that the person speaks. Person identification is
performed by tracking mouth movements of the talking face and by estimating
the likelyhood of each model of having generated the observed sequence of
features. The model with the highest likelyhood is chosen as the recognized
person.
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