2. .

3. A facial recognition system is a computer application for
automatically identifying or verifying a person from a digital
image or a video frame from a video source. One of the ways
to do this is by comparing selected facial features from the
image and a facial database.
It is typically used in security systems and can be compared to
other biometrics such as fingerprint or eye iris recognition
system.

5.  It requires no physical interaction on behalf of the user.
 It does not require an expert to interpret the comparison
result.
 Identify a particular person from large crowd.
 Verification of credit card, personal ID, passport.

7.  Different methods of face recognition.
 Feature extraction methods
 Holistic methods
 Hybrid methods

8. Every face has at least 80 distinguishable parts called
nodal points. Some of them are:

9. Every face has at least 80 distinguishable parts called
nodal points. Some of them are:
1. Distance between the eyes

10. Every face has at least 80 distinguishable parts called
nodal points. Some of them are:
1. Distance between the eyes
2. Width of the nose

11. Every face has at least 80 distinguishable parts called
nodal points. Some of them are:
1. Distance between the eyes
2. Width of the nose
3. Depth of eye sockets

12. Every face has at least 80 distinguishable parts called
nodal points. Some of them are:
1. Distance between the eyes
2. Width of the nose
3. Depth of eye sockets
4. Structure of cheek bones

13. Every face has at least 80 distinguishable parts
called nodal points. Some of them are:
1. Distance between the eyes
2. Width of the nose
3. Depth of eye sockets
4. Structure of the cheek bones
5. Length of jaw line

14. A general face recognition software conducts a comparison of these
parameters to the images in its database.
Depending upon the matches found, it determines the result.
This technique is known as feature based matching and it is the most basic
method of facial recognition.

16. The only way to overcome this challenge is better equipment, i.e.
basically , use of high tech cameras.
It is very much essential for the system to catch the image
accurately.

19. The only way to overcome this challenge is better
ALGORITHMS for facial recognitions. If the systems are
programmed for every possible permutation and combination of
the image, an accurate match can be achieved.
Some algorithms that try to overcome this problem are as
follows:
-Half-face based algorithm
-Perturbation Space Method(PSM).
-Local binary pattern
-Neural network, etc.

20. PSM algorithm that converts two dimensional image (e.g.
photographs into three – dimensions (such a process is called
“Morphing”).
The three – dimensionsional representation of the head
are then rotated in
Both the left-to-right and up-and down directions.

21. The facial recognition equipment used for basic
surveillance purpose has 3 important components.
1. The camera or scanning device
2. Infrared illuminator
3. An efficient software

22. An IR-illuminator is a device that emits infrared light-low frequency
electromagnetic radiation that's outside the visible spectrum. In other words, it
gives off light that a camera can pick up and use, but that a person can't see-so
while it's still dark to the human eye, the camera can see just fine.
There are 3 main types of infrared illuminators namely diodes, lamps & lasers.

23. Facial recognition is a very useful mechanism when it comes to office
related user identification. One such example is a product of Havon
industries called FaceID.
Face ID is industry first embedded facial recognition system with leading
“Dual Sensor” Facial Recognition Algorithm, which designed for
application like physical access control and time attendance, identity
management and so on.

24. In around 10 years from now, it is being estimated that facial
recognition technology will be the backbone of all major security,
home and networking service. With the growth of social
networking over the web, unbelievably accurate facial recognition
algorithms and advanced equipment, a person’s face, no mater
ageing or disguises or damage, can be recognized and data about
that person can be produced.
Here is a small glimpse of what facial recognition technology
would make of the future social networking….

25. Assuming amazing resolutions, facial and object
recognition, this is how social networking would be in
the future….

26. Pros:
1.Better security systems.
2.Easy user verifications.
3.Greatly reduces current load on security and judicial systems.
Cons:
1.Privacy issues.
2.Even helps in kidnapping!
3.Errors in detection may cause inconvenience to innocent users.

27. • Counting of people in a
room (e.g. for
temperature adjustment)
• Domestic security systems
• Police surveillance
• Domestic Computer / phone identification
systems
• Employee management systems in Companies.
• National and International security systems.

30. 1. W. Bledsoe. Man-machine facial recognition
2. T. Kanade Computer Recognition of Human Faces
3. www.wikipedia.com
4. www.authorstream.com
5.www.howstuffworks.com
6. www.inttelix.com
7. www.face-rec.org
8. www.facialrecognitionsolution.com
9. www.facedetection.com