This document discusses various biometric technologies including fingerprint recognition, iris scanning, retina scanning, voice recognition, signature verification, face recognition, and hand geometry recognition. It describes how each type of biometric works, including capturing biometric data, extracting distinguishing features, enrollment, verification, and matching against stored templates. Biometrics are increasingly used for identification and access control because they cannot be lost, stolen, or forgotten like ID cards or passwords. However, biometric systems must also account for changes in biometrics over time.

1. Biometric Technology
Presented By:
• Prapti Mitra
• Abhishek Mitra
• Shinjan Karmakar
• Sudip Sadhukhan

2. What is Biometric?
Biometrics is the measurement and statistical analysis of people's physical and
behavioral characteristics. The term "biometrics" is basically derived from the
Greek word "bio" meaning life and "metric" meaning to measure.

3. Types of biometric devices:
 Chemical biometric devices
 Visual biometric devices
 Behavioral biometric devices
 Olfactory biometric devices
 Auditory biometric devices

4. Why biometrics?
 Biometrics cannot be lost, stolen or forgotten. Barring disease or
serious physical injury, the biometric is consistent and permanent.
 Biometric recognition provides a strong link between an
individual and a claimed identity. One area where biometrics can
provide substantial help is in guarding against attempts to
establish fraudulent multiple identities or prevent identity fraud.
 There is no requirement to remember passwords or PINs thus
eliminating an overhead cost. The biometric is always available to
the individual.
 Biometric itself cannot be socially engineered, shared or used by
others.

5. Working of biometric system
 Capturing
 Pre-processing
 Feature extraction
 Template matching
 Matcher/Comparison
 Application Device

6. STAGES of biometric verification
There are basically two most important steps of biometric verification:
 Enrollment
 Authentication

7. Various biometrics technologies
• Fingerprint Recognition • Voice Recognition
• Iris Recognition
• Retina Recognition
• Signature Verification
• Hand print Geometry
• Facial Recognition

8. Iris scanner
 Iris scanner measures the iris pattern of the eye i.e. the coloured
part of the eye that surrounds the pupil.
 The iris scanner analyzes features like rings, furrows and freckles
existing in the coloured tissue surrounding the pupil.
 Iris pattern is not changed over years or by glasses, contact lens.
 Iris scanning is used to identify a person according to their unique
pattern, but they tend to be far costlier and more complex.
 The biggest advantage of iris scanning is its accuracy and
reliability.

9. Iris scanning technology
Iris recognition uses camera technology with
subtle infrared illumination to acquire images
of the detail-rich, intricate structures of the iris.
Digital templates encoded from these patterns
by mathematical and statistical algorithms
allow unambiguous positive identification of an
individual. Database of enrolled templates are
searched and they are verified.

10. Retina Scanner:
 Retina scanner is used to map the unique patterns
of person's retina.
 Retinal Biometrics is a sophisticated means for
identifying people by the pattern of blood vessels
on the retina.
 Retina scanning is used to identify a person
according to their unique pattern , but they tend to
be far costlier and more complex.
 Retinal scanning is highly accurate.

11. Working process of retina scanner
Retinal scan is performed by casting an unperceived light
beam of low energy infrared light into a person's eye as they
look through the scanner's eyepiece. This beam of light traces
a standardized path on the retina. Because the retinal vessels
are more absorbent of this light than the rest of the eye, the
amount of reflection varies during the scan. The pattern of
variations is converted to computer code and compared with
the existing data.

12. Flow chart of retina scanner

13. Fingerprint Recognition
 Fingerprint recognition or fingerprint authentication refers to the automated
method of verifying a match between two human fingerprints
 The three basic patterns of fingerprint ridges are the arch, loop, and whorl
 The analysis of fingerprints for matching purposes generally requires the
comparison of several features of the print pattern. These include patterns,
which are aggregate characteristics of ridges, and minutia points, which are
unique features found within the patterns. It is also necessary to know the
structure and properties of human skin in order to successfully employ some of
the imaging technologies.
 A fingerprint sensor is an electronic device used to capture a digital image of
the fingerprint pattern. The captured image is called a live scan. This live scan
is digitally processed to create a biometric template (a collection of extracted
features) which is stored and used for matching.

14. Process of Fingerprint recognition

15. Voice recognition
 Voice Recognition or Speaker Recognition is a biometric process
of validating a user's claimed identity using characteristics
extracted from their voices.
 It uses the pitch, pattern, tone, frequency, rhythm of speech for
identification purposes.
 With the help of special voice recognition software, tiny
differences in each person’s voice can be noted, tested, and
authenticated to only allow access to the person that has the right
tone, pitch, and volume of voice.
 It has added another layer of security for computer systems. It
produces a more efficient and cost effective environment.

16. Process of voice recognition
 The most common approaches to voice recognition can be divided into two
classes: "template matching" and "feature analysis".
 During the enrollment phase, the spoken words are converted from analog to
digital format, and the distinctive vocal characteristics such as pitch, frequency,
and tone, are extracted, and a speaker model is established.
 A template is then generated and stored for future comparisons.

17. Signature verification
 1.Verify user signatures using computers or embedded
devices
 In signature verification the velocity of sign, width of
sign and the pressure of sign is verified.
 Signature verification software protects us against
fraud and reduces costs. Since all signatures are
unique, they are relied upon for verification by
financial organizations, businesses and governments
to authorize transactions and documents

18. Difference
 Static/Offline
1. Early 1970’s
2. Only image of signature
3. No need of special hardware, ubiquitous
use
4. Large storage
5. Can not trace speed, style, pressure etc
6. Easier to forge
7. Around 95% accuracy
 Dynamic/Online
1. Early 1990’s
2. Uses shape, speed, pressure
3. Needs special digital surface, pads and
pen etc.
4. Numeric data, small storage
5. Can use speed, pressure, angle of pen etc
to further exploit individuality
6. Harder to forge
7. Around 99% accuracy

19. Capture Devices
 Technology
 Pressure sensitive sensors arranged in compact grid to form flat surface
 When pen touches a sensor, pressure at that sensor is calculated
 The sensors are scanned periodically for pen positions
 Position of sensor, pressure, pen angle are stored
 Periodic scanning results in sequence of parameters

20. Face Recognition Technology
 A face recognition system is a computer application capable of identifying or
verifying a person from a digital image or a video frame from a video source.
One of the ways to do this is by comparing selected facial features from the
image and a face database.
 Face recognition can also identify slightly different placing of the eyebrows,
the width of the eyes, or the breadth of the nose with the position/size/shape of
the eyes, nose, cheekbones and jaw line.
 Facial recognition is one of the most common biometrics used by humans. And
this is basically a visual biometric device.

21. Face Recognition
1. Capture image
2. Find face in image
3. Extract features (store template)
4. Compare templates
5. Declare matches

22. Face Detection Algorithm

23. hand geometry
 Hand geometry is essentially based on the fact that virtually
every individual's hand is shaped differently than another
individual's hand and which over the course of time the shape
of the person's hand does not significantly change
 This includes the width and length of our palm, the width and
length of our fingers, the distance between each knuckle, and
the depth of each of the lines in our palm. This is more
complex than regular fingerprint scanning, and will be much
more accurate with less chance of falsification

24. working process hand geometry
There are two stages in hand geometry recognition:
1. Enrollment
2. Verification

25. disadvantages
 Lack of standardization
 While the reliability and the accuracy of biometric devices
continues to improve.
 Biometric systems must be able to accommodate changes to the
biometric over time which may be caused by ageing, illness or
injury.
 The effectiveness of the sample collection process is strongly
influenced by environmental conditions, user training and
usability. For example, lighting, facial orientations, expression,
image resolution and the wearing of hats can affect the quality of
the sample.

26. conclusion
The upcoming lead in technology

27. References:
 Wikipedia
 www.slideshare.com
 www.powershow.com
 www.google.com