This document presents an overview of biometrics by Vishwajeet and Adothu Rambabu from the National Institute of Technology in Jamshedpur, India. It defines biometrics as identifying individuals based on physiological or behavioral traits. It discusses various biometric methods including fingerprints, face recognition, retina scanning, and others. It explains how biometric systems work by capturing samples, extracting data, comparing to templates, and matching or non-matching. The document also reviews advantages and disadvantages of different biometric techniques and their applications.

1. BIOMETRICS
PRESENTED BY
VISHWAJEET & ADOTHU RAMBABU
ROLL NO – 467/11 & 537/11
NATIONAL INSTITUTE OF TECHNOLOGY
JAMSHEDPUR, INDIA – 831014

2. INTRODUCTION
 Biometrics refers to the automatic identification of a
person based on his or her physiological or behavioral
characteristics.
 Biometrics is an accurate method of authentication that
uses the physiological and biological traits of a person to
verify and establish their identity.

3. PHYSIOLOGICAL AND/OR BEHAVIORAL
CHARACTERISTICS
 Behavioral:
 Voice
 Keystroke
 Signature
 Physiological:
 Fingerprint
 Hand
 Eyes (Iris , Retina)
 DNA
 Face

4. BIOMETRICS

5. BIOMETRICS: WHY?
 Eliminate memorization –
◦ Users don’t have to memorize features of their voice, face, eyes, or fingerprints
 Eliminate misplaced tokens –
◦ Users won’t forget to bring fingerprints to work
 Can’t be delegated –
◦ Users can’t lend fingers or faces to someone else
 Often unique –
◦ Save money and maintain database integrity by eliminating duplicate enrollments

6. WORKING OF BIOMETRICS TECHNOLOGY
ALL BIOMETRIC SYSTEMS WORKS IN A FOUR-STAGE PROCESS THAT CONSISTS OF
THE FOLLOWING STEPS:
• CAPTURE : A Biometric system collects the sample of biometric features like
fingerprint, voice etc of the person who wants to login to the system.
• EXTRACTION: The data extraction is done uniquely from the sample and a template is
created. Unique features are then extracted by the system and converted into a digital
biometric code. This sample is then stored as the biometric template for that individual.
• COMPARISON: The template is then compared with a new sample. The biometric data
are then stored as the biometric template or template or reference template for that
person.
• MATCH/NON-MATCH: The system then decides whether the features extracted from the
new sample are a match or a non-match with the template.

7. SIGNATURE SCAN
 Measures speed, pressure, stroke order an image of signature.
 Non-repudiation
 Mainly used for verification
# PROBLEMS:
 Forgers could reproduce

8. VOICE VERIFICATION
Measures the sound waves of human speech.
 pitch, intensity, quality and duration.
 user talks to a microphone a passphrase.
 voice print is compare to a previous one.
#PROBLEMS:
 include background noise

9. KEYSTROKE SCAN
Measures the time between strokes and duration of key pressed.
 Most commonly used in systems where
keyboard is already being used.

10. FINGER PRINT RECOGNITION
Fingerprint verify the authenticity of the individual.
Among all the biometric techniques, fingerprint-based identification is the oldest
method that has been successfully used in numerous applications.
Everyone is known to have unique, immutable
fingerprints. A fingerprint is made of a series of
ridges and furrows on the surface of the finger.
# Advantage:
Low storage space required compared to
other ones.

11. RETINA RECOGNITION
 Scan the retina to authenticate the identity of a person.
 Unique to each person.
 Unique to each eye.
 Highly reliable because no two people have
the same retinal pattern.
# Problems:
1. It has extremely low acceptance rate .
2. Measurement accuracy can be affected by a disease
3. Not very user friendly

12. FACIAL RECOGNITION
 Location and position of facial features.
 Distance between the eyes.
 Distance between the eyes and nose ridge.
 Angle of a cheek.
 Slope of the nose.
 Facial temperatures.

13. HAND SCAN
Typical systems measure 90 different features:
 Overall hand and finger width
 Distance between joints
 Bone structure
Primarily for access control:
 Machine rooms
 Olympics
Strengths:
 No negative connotations – non-intrusive
 Reasonably robust systems
Weaknesses:
 Accuracy is limited; can only be used for 1-to-1 verification
 Bulky scanner

14. TEMPLATE SIZE
Biometric Approx. Template Size
Voice 70k – 80k
Face 84 bytes – 2k
Signature 500 bytes – 1000 bytes
Fingerprint 256 bytes – 1.2k
Hand Geometry 9 bytes
Iris 256 bytes – 512 bytes
Retina 96 bytes

15. Advantages :
 Biometric attributes are unique and these can’t be faked or interchanged so,
this uniqueness imparts a high level security to these systems.
 There is no need for remembering passwords, pin’s etc.
Disadvantages :
 Biometric template data consume more space than the conventional user
id/password combinations.
Advantages & Disadvantages

16. APPLICATIONS
Commercial
 Computer login
 Electronic payment
 ATMS
Government
 Passport control
Forensic
 Missing persons
 Criminal investigations

17. BIOMETRIC MARKET SHARE

18. References
 Biometrics.gov.
http://www.biometrics.gov/ReferenceRoom/Introduction.aspx
 Jain, Anil K., Arun Ross, and Salil Prabhakar. "An Introduction to Biometric Recognition."
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 14.1
(2004): 4-20. IEEE Xplore.
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1262027
 Jain, Anil K., Patrick J. Flinn, and Arun A. Ross. Handbook of Biometrics. New York: Springer.
http://libcat.clemson.edu/record=b2478857
 Phillips, Jonathon P., Alvin Martin, C. L. Wilson, and Mark Przybocki. "An Introduction
Evaluating Biometric Systems." Computer 33.2 (2000): 56-63. IEEE Xplore.
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=820040
 http://bprl.cs.clemson.edu/about.html
 http://bprl.cs.clemson.edu/projects.html

19. Thank you