This document summarizes a seminar presentation on face recognition technology. It begins with an introduction to facial recognition systems and what biometrics are. It then discusses why facial recognition is chosen over other biometrics, the differences between facial recognition and face detection, and how facial recognition systems work. Application areas are identified, such as security, government ID, casinos. Advantages include convenience and cost-effectiveness, while disadvantages include issues with lighting, pose, and privacy concerns. The growth rate of the facial recognition market is projected to be nearly 14% annually through 2022.

1. Seminar
on
“Face Recognition Technology”
Presented by-: Shubham Lamichane
College :GBPIET Pauri
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2. Contents
1.Introduction
2.What are Biometrics
3.Why do we choose FRS over
other Biometrics
4.Difference between FRS and FDS
4.Face Recognition
6.How FRS works
7.Example
8.Application area
9.Few applications
10.Advantages
11.Disadvantages
12.Application in India
13.Growth rate
14.References
15.Conclusion
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3. Introduction
 A facial recognition system is a computer application capable
of identifying or verifying a person from a digital image or
a video frame from a video source.
 Source: www.medicalnewstoday.com/articles/320316.php
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4. What are Biometrics?
 A biometrics is a unique, measurable characteristic of a human being that
can be used to automatically recognize an individual or verify an
individual identity.
Physiological Biometrics :
a. Finger-scan
b. Facial Recognition
c. Iris-scan
d. Retina-scan
e. Hand-scan
Behavioural Biometrics:
a. Signature
b. Voice 4

5. Why we choose face recognition over
other biometric ?
 There are number reasons to choose face recognition. This includes the
following :
 a. It requires no physical interaction on behalf of the user.
 b. It is accurate and allows for high enrolment and verification rates.
 c. It does not require an expert to interpret the comparison result.
 d. It can use your existing hardware infrastructure, existing cameras and
image capture devices will work with no problems.
 e. It is the only biometric that allow you to perform passive identification.
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6. Difference between facial recognition and face
detection
face detection face recognition
source:www.google.com
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7. FACE RECOGNITION
 A facial recognition system is a computer application capable
of identifying or verifying a person from a digital image or a video frame from
a video source
 For face recognition there are two types of comparisons
1. Verification(1:1 mapping)
This is where the system compares the given individual with who that
individual says they are and gives a yes or no decision.
2. Identification(1:N mapping)
This is where the system compares the given individual to all the Other
individuals in the database and gives a ranked list of matches.
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8. All identification or authentication technologies operate
using the following four stages:
 1.Capture
 2.Extraction
 3.Comparision
 4.Match/Non
Match
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9. COMPONENTS OF FACE RECOGNITION
SYSTEMS
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10. IMPLEMENTATION OF FACE RECOGNITION
TECHNOLOGY
 The implementation of face recognition technology includes the followingthree stages:
1. Data acquisition
2. Input processing
3. Face image classification and decision making
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11. 1.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 usageof
photographs to gain unauthorized access.
2. 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 facesor
face in a scene must be detected. Once the face is detected, it must be localized.
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12. 3.Face image classification and decision
making
A newly recorded pattern is pre-processed and compared with each face print stored
in the database. As comparisons are made, the system assigns a value to the
comparison using a scale of one to ten. If a score is above a predetermined threshold,
a match is declared.
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13. HOW FACE RECOGNITION SYSTEMS
WORK
 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.
Software defines these landmarks as nodal points.
 There are about “80 nodal points” on a human face.
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14. Nodal points
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15. Here are few nodal points that are measured by the
faceit software.
 distance between the eyes
 width of the nose
 depth of the eye socket
 cheekbones
 jaw line
 chin
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16. Face recognition algorithms:
 Principal component analysis
 3-D Face Recognition
 Support Vector machine
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17. An Example of FRS
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18. Application area
Enterprise Security Computer and physical access control
Government Events Criminal Terrorists screening; Surveillance
Immigration/Customs
Illegal immigrant detection; Passport/ ID Card
authentication
Casino Filtering suspicious gamblers /VIPs
Toy Intelligent robotic
Vehicle Safety alert system based on eyelid movement
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19. Few Applications
 1.Facebook auto-tag feature
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20.  2.Attendance management system:
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21.  3.Criminal identification
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22. 4.Payment
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23. 5.Face ID
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24. Advantages
 There are many benefits to face recognition systems such as its
convenience and Social acceptability.
 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.
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25. Disadvantages
 Face recognition systems can not tell the difference between
identical twins.
 the illumination problem, the pose problem, scale variability,
images taken years apart, glasses, moustaches, beards, low quality
image acquisition, partially occluded faces, etc.
 Privacy concern.
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26. Application in India
 Face authentication will be
enabled by July to help people
facing any difficulty in the
authentication of their
fingerprints, which may be
worn out because of age or
hard work, or other factors,
said the UIDAI or Unique
Identification Authority of
India.
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27. Growth Rate
 The global facial recognition market is expected to grow from USD 4.05
billion in 2017 to USD 7.76 billion by 2022, at a Compound Annual Growth
Rate (CAGR) of 13.9% during forecast period.
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28. Conclusion
Face recognition technologies have been associated generally with very costly
top secure applications. Today the core technologies have evolved and the cost of
equipment is going down dramatically due to the integration and the increasing
processing power. Certain applications 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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29. References
 www.prnewswire.com
 en.wikipedia.org
 www.ieee.com
 electronics.howstuffworks.com
 www.techclinch.com
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