BIOMETRICS THE MAN MACHINE INTERFACE

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Presentation transcript:

BIOMETRICS THE MAN MACHINE INTERFACE

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

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

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

APPROACH TO DYNAMIC SIGNATURE Graphic Depiction of Dynamic Signature Characteristic.

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

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

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

EBGM: Elastic Bunch Graph Matching Elastic Bunch Map Graphing.

IRIS RECOGNITION Iris Diagram. Iris Structure.

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

Iris vs. Retina Recognition Structure of the Eye.

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.

REFERENCES www.biometrics.dod.mil/ www.ifpo.org/articlebank/biometrics.html www.questbiometrics.com www.toodoc.com/biometrics-ppt.html

QUERIES…???