Face recognition technology uses digital images and video frames to automatically identify or verify a person. It works by comparing selected facial features from an image to a facial database containing 80 landmarks on each face, such as distance between eyes, width of nose, and jaw lines. This is done using local feature analysis algorithms to encode faces and create unique numerical codes, or "face prints", that can be matched against large databases. While face recognition provides convenience over other biometrics like fingerprints, it has disadvantages such as an inability to distinguish identical twins and potential issues with database searching speeds. However, decreasing costs are leading to more widespread deployment of this technology in applications like access control, advertising, and retail point-of-sale systems.

1. By
P. Shashidhar Reddy

2. What do you mean by Face Recognition
Technology???
A technology Which is used to automatically identify or
verify a person from a Digital Image or a Video Frame
from Video Source
One of the way to do this is by comparing selected
Facial Features from the Image and the Facial Database

3. What is Behind Face Recognition???
 How is it Possible??

4. 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

5. Biometrics can be measure in both Physiological and Behavioral
Characteristics
Physiological Characteristics:
1. Finger- Scan
2. Iris Scan
3. Retina Scan
4. Hand Scan
5. Facial Recognition
80 landmarks on a human face.
oDistance between eyes
oWidth of the nose
oDepth of the eye socket
oCheekbones
oJaw lines
oChin

6. Behavioral Characteristics:
Behavioral biometrics (based on measurements and data derived
from an action) include:
1. Voice Scan
2. Signature Scan
3. Keystroke

7. Why we choose face recognition
over other biometric?
 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

8. What is behind this Technology
 The heart of this facial recognition system is the Local
Feature Analysis (LFA) algorithm.
 This is the mathematical technique the system uses to
encode faces
 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.

9. Face recognition: Procedure
Input face
image(Capture)
Face feature
extraction
Feature Matching Decision maker
Output result

10. 1. Eigen face or PCA (Principal Component Analysis)
2. EBGM -Elastic Bunch Graph Method.-2D Image
3. 3D Face Recognition Method.-3D Image
Face Feature Extraction Methods

11. Access Control Products
Access Control into Bank
Kiosk Lyon Airport,
France
New Face
Reader with
LCD Face Reader with
mirror -ATM

12. Advantages:
 Convenience and social acceptability
 Easy to use
 Inexpensive

13. Disadvantages:
 Face recognition systems can’t tell the difference
between identical twins

14. Future of Face Recognition
 Billboard with face recognition –Advertising
 Face base Retailing-(Shopping)
retail stores, restaurants, movie theaters, car rental
companies, hotels. (You Can pay the bills using your face)
 Recognition Twins
 More High Speed accessing of Database

15. Conclusion:
Face recognition technologies have been associated
generally with very costly top secure applications. Today
the core technologies have evolved and the cost of
equipments 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

16. Quaries??

17. Thank You.