1. FACE RECOGNITION TECHNOLOGYBy
N.NAGOORVALI (07U51A0465)

2. INTRODUCTION
Complex and largely software based technique
Analyze unique shape, pattern &positioning of facial features
It compare scans to records stored in central or local database or even on a smart card

3. WHAT IS BIOMETRICS?
It is a unique measurable characteristics of a human being
Used to automatically recognize an individual’s identity
Two types 1.physiological &
2. behavioral characteristics
A “biometric system” refers to integrated hardware and software used to conduct biometric identification

4. WHY WE CHOOSE FACE RECOGNITION OVER OTHER BIOMETRICS
It requires no physical interaction on behalf of user
It is accurate and allows for high enrolment and verification
Not require an expert to interpret the comparison result
Can use your existing infrastructure
Passive identification

5. FACE RECOGNITION Two types of comparison in face recognition
1.Verification- The system compare the given individual with who that individual says they are.
2.Identification-The system compares a given individual to all the other individuals in the database and gives a ranked list of matches.

6. STAGES OF IDENTIFICATION
Match/Non
match
Extraction
Comparison
Capture
Accept/Project

7. FOUR STAGES OF IDENTIFICATION
Capture-Capture the behavioral sample
Extraction-unique data is extracted from the sample and a template is created.
Comparison-the template is compared with a new sample.
Match/non match-the system decides whether the new samples are matched or not.

8. 3D GRAPHICAL MODELS OF FACES

9. COMPONENTS OF FACE RECOGNITION
Enrollment module-An automated mechanism that scans and captures a digital or analog image of a living personal characteristics
Database-Another entity which handles compression ,processing ,data storage and compression of the captured data with stored data
Identification module-The third interfaces with the application system

10. Face Face rag & scoring Segmentation Analysis Enrollment Module
Preprocessing
&
segmentation
Analysis
Analysis
Data
User
Interface
System
Data base
Face
Verification Module
Preprocessing&
Segmentation
Face rag & scoring
Analysis
reject

11. PERFORMANCE False Acceptance Rate [FAR] False Rejection Rates [FRR]
Response time
Threshold/decision Threshold
Enrollment time
Equal error rate

13. THE SOFTWARE
Detection
Alignment
Normalization
Representation
Matching

15. ADVANTAGE DISADVANTAGE Convenience and social acceptability
Easy to use
Inexpensive biometric
DISADVANTAGE
Face recognition systems can’t tell the difference between
identical twins

16. APPLICATIONS Government Use Commercial Use 1.Day care
1. Law enforcement
2.Security/counterterrorism
3.Immigration
Commercial Use
1.Day care
2.Residential security
3.Voter verification
4.Banking using ATM

17. 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.

18. THANK YOU