1. Head of department -Sabina Ansari Case study teacher
-Priyanka pawar LAXMAN DEVRAM SONAWANE COLLEGE
2. Case study on Face recognition in e-attendance
3. Overview Introduction History What are biometrics Why we
choose face recognition over other biometrics What is face
recognition Components of face recognition How facial recognition
system works Where face recognition technology is used Future of
face recognition
4. Introduction In today's networked world, the need to
maintain the security of information or physical property is
becoming both increasingly important and increasingly difficult.
Face recognition is one of the few biometric methods that possess
the merits of both high accuracy & 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.
5. History The first attempts to use face recognition began in
the 1960s with a semi-automated system. Marks were made on
photographs to locate the major features; it used features such as
eyes, ears, noses, and mouths. Then distances and ratios were
computed from these marks to a common reference point and compared
to reference data. In 1970s, Goldstein and Harmon used 21 specific
subjective markers such as hair color and lip thickness to automate
the recognition. This proved even harder to automate due to the
subjective nature of many of the measurements still made completely
by hand.
6. What are biometrics A biometric is a unique, measurable
characteristic of a human being that Can be used to automatically
recognize an individual or verify an individuals identity.
7. Biometrics can measure both physiological and behavioral
characteristics Physiological biometrics:- This types of biometrics
is based on measurements and data derived from direct measurement
of a part of the human body. Behavioral biometrics:- This types of
biometrics is based on measurements and data derived from an
action.
9. 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. It can use your existing
hardware infrastructure, existing cameras and image capture,
devices will work with no problems. It is the only biometric that
allow you to perform passive identification in one to Many
environments (e.g.: identifying a terrorist in a busy Airport
terminal.
10. What is face recognition Face recognition is one of the few
biometric methods that possess the merits of both high accuracy and
low intrusiveness. A facial recognition system is a computer
application for automatically identifying or verifying a person
from a digital image from the source, One of the ways to do this is
by comparing selected facial features from the image and a facial
database.
11. Detection two-class classification. Face vs. Non-face.
Recognition multi-class classification. One person vs. all the
others. Difference between face detection and recognition
12. Two types of comparison in face recognition Face
Verification: The system compares a face image that might not
belong to the database, verify whether it is from the person it is
claimed to be in the database. Face Identification: The system
compares a face image that belongs to a person in a database, tell
whose image it is.
13. Stages of identification Capture Extraction Comparison
Match/Non match Accept/Project 1 2 3 4 5 Capture- Capture the
behavioral and physical 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.
14. 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.
15. How facial recognition system works Facial recognition
software is based on the ability to first recognize faces, which is
a technological feat in itself. If you look at the mirror, you can
see that your face has certain distinguishable landmarks. These are
the peaks and valleys that make up the different facial features.
VISIONICS defines these landmarks as nodal points. There are about
80 nodal points on a human face.
16. distance between the eyes width of the nose depth of the
eye socket cheekbones jaw line Nodal points that are measured by
the software
17. Detection- when the system is attached to a video
surveillance system, the recognition software searches the field of
view of a video camera for faces. If there is a face in the view,
it is detected within a fraction of a second. A multi-scale
algorithm is used to search for faces in low resolution. The system
switches to a high- resolution search only after a head-like shape
is detected. Alignment- Once a face is detected, the system
determines the head's position, size and pose. A face needs to be
turned at least 35 degrees toward the camera for the system to
register it. Normalization-The image of the head is scaled and
rotated so that it can be registered and mapped into an appropriate
size and pose. Normalization is performed regardless of the head's
location and distance from the camera. Light does not impact the
normalization process.
18. Representation-The system translates the facial data into a
unique code. This coding process allows for easier comparison of
the newly acquired facial data to stored facial data. Matching- The
newly acquired facial data is compared to the stored data and
(ideally) linked to at least one stored facial representation.
19. Advantages and disadvantages ADVANTAGES Convenient, social
acceptability. More user friendly. Inexpensive technique of
identification. DISADVANTAGES Problem with false rejection when
people change their hair style, grow or shave a beard or wear
glasses. Face recognition systems cant tell the difference between
identical twins.
20. Where face recognition technology is used Airports and
railway stations Voter verification Cashpoints Stadiums Public
transportation Financial institutions Government offices Businesses
of all kinds
21. Future of face recognition Some consider the problem
impossible. Advancements in hardware and software. Slow integration
into society in limited environments. Very large potential
market.
22. CONCLUSION Face recognition technologies have been
associated generally with very costly top secure applications.
Today the core technologies have evolved and the cost of
equipment's is going down dramatically due to the integration and
the increasing processing power. Certain applications of face
recognition technology are now cost effective, reliable and highly
accurate. As a result there are no technological or financial
barriers for stepping from pilot project to widespread deployment.
For implementations where the biometric system must verify and
identify users reliably over time, facial scan can be a very
difficult, but not impossible, technology to implement
successfully.