FACE RECOGNITION TECHNOLOGY By N.NAGOORVALI (07U51A0465)

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

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

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

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.

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

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.

3D GRAPHICAL MODELS OF FACES

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

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

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

THE SOFTWARE Detection Alignment Normalization Representation Matching

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

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

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.

THANK YOU