1. BIOMETRICS THE MAN MACHINE INTERFACE

2. INTRODUCTION BIOMETRICS – definition.
Biometric system comprised of Integrated components like :
Sensor.
Signal processing algorithms.
Data storage.
Matching algorithm.
Decision process.

3. BIOMETRIC MODALITIES
Biometric modalities include fingerprint, face, iris, voice, signature and hand geometry etc..
Implementing a biometric device including location, security risks etc..

4. DYNAMIC SIGNATURE
Various measurements are observed and processed for comparison.
Dynamic Signature Depiction: As an
Individual signs the contact sensitive tablet.

5. APPROACH TO DYNAMIC SIGNATURE
Graphic Depiction of Dynamic Signature Characteristic.

6. FACE RECOGNITION Predominant Approaches :
Principal Components Analysis (PCA).
Linear Discriminant Analysis (LDA).
Elastic Bunch Graph Matching (EBGM).

7. PCA: Principal Components Analysis
Standard Eigenfaces: Feature vectors are derived using Eigenfaces.

8. LDA: Linear Discriminant Analysis
Example of Six Classes Using LDA.

9. EBGM: Elastic Bunch Graph Matching
Elastic Bunch Map Graphing.

10. IRIS RECOGNITION
Iris Diagram.
Iris Structure.

11. APPROACH TO IRIS RECOGNITION
White outlines indicate the localization
of the iris and eyelid boundaries.
Pictorial Representation of Iris Code.

12. Iris vs. Retina Recognition
Structure of the Eye.

13. CONCLUSION
Biometrics provides high security and reduces the incidence of unauthorized access in sensitive areas.
Biometrics cannot be lost, stolen or forgotten.
More secure than a long password.

14. REFERENCES www.biometrics.dod.mil/

15. QUERIES…???