What Is It? Why Biometrics?

collarlimabeansSécurité

23 févr. 2014 (il y a 3 années et 5 mois)

113 vue(s)

Samantha L. Allen

Dr. Damon L. Woodard

July 31, 2012

BIOMETRICS:

EAR RECOGNITION

I.
Biometrics: What
Is
It?


II.
Why Biometrics?


III.
Ear Biometrics


IV.
How A Biometric System
Works


V.
Conclusion


OUTLINE

Biometrics


The science and technology of measuring and analyzing
biological data


Measures and analyzes human body characteristics for
authentication


Physical or behavioral characteristics


Identity access management and access control

WHAT IS IT?


Keystroke


Voice patterns


Gait


Signature

BEHAVIORAL CHARACTERISTICS


DNA


Fingerprints


Eye retinas and irises


Facial patterns


Hand measurements


Ear geometry


PHYSICAL CHARACTERISTICS

BIOMETRIC SYSTEM
COMPONENTS

Sensor

Feature
Extraction

Matcher

DATABASE


Identity Claimed


One
-
to
-
one Comparison


Authentication is either
approved or denied.


No identity claimed


One
-
to
-
many comparison


Identity is determined


(OR)


User not being enrolled leads
to fail of identification.


Verification

Identification

BIOMETRIC SYSTEM OPERATION


Biometrics is a method of
*direct*
human identification as opposed
to identifying humans by their possession of keys or remembering
passwords
.



P
referred method of identification because ID’s and cards can easily
be stolen and passwords are likely to be forgotten or shared.



Discourages fraud



Enhances security

WHY BIOMETRICS


Privacy Concerns



Irrevocable



Functional Creep



Output is “matching score” instead of yes/no

DISADVANTAGES TO BIOMETRICS



Permanence


Performance


Acceptability


Distinctiveness


Circumvention


Collectability


Universality

BIOMETRIC SELECTION PROCESS



Dates back to the 1980’s


Shape and features of ear


Unique


Invariant with age



Disadvantages


Affected by occlusions, hair,


and ear piercings

EAR BIOMETRICS BACKGROUND

EXAMPLES OF BAD IMAGES





Performance is greatly
affected by pose variation
and imaging conditions


Images contain less
information





Contains surface shape
information related to
anatomical structure


Relatively insensitive to
illumination


Slightly higher performance

2D VS. 3D EAR BIOMETRICS


Approaches


Global: Whole ear



Local: Sections of ear



Geometric:
Measurements

EAR BIOMETRICS APPROACHES


Has this applicant been here before?



Is this the person that he/she claims to be?



Should this individual be given access to our system?



Are the rendered services being accessed by a legitimate user
?

HOW A BIOMETRIC SYSTEM
WORKS

HOW A BIOMETRIC SYSTEM
WORKS (CONT.)


Identifying features of individual are enrolled into system.


During feature extraction, the application is used to identify
specific points of data as match points


Match points in database are processed using an algorithm
that translates the information into numeric values or
feature vectors.


Feature set is compared against the template set in the
system database.

HOW A BIOMETRIC SYSTEM
WORKS (CONT.)


Human ear detection is
a crucial task
of a human
ear
recognition
system
because
its performance
significantly
affects
the overall quality of the system
.


template matching based
detection


ear shape model based
detection


fusion
of color
and range images and global
-
to
-
local
registration based
detection



EAR RECOGNITION

DETECTION PROCESS

The following are used as performance metrics for biometric
systems:


False
accept rate or false match rate (FAR or
FMR)


Measures
the percent of invalid inputs which are incorrectly accepted
.


Probability that the system incorrectly matches the input pattern to a non
-
matching template in the database.


False reject rate or false non
-
match rate (FRR or FNMR)


M
easures
the percent of valid inputs which are incorrectly
rejected.


P
robability
that the system fails to detect a match between the input
pattern and a matching template in the database.

PERFORMANCE METRICS


Research included exploration of ear recognition
implementation in Matlab.


100 pre
-
processed images, 17 subjects


SUMMER RESEARCH


Enroll images into database
with different classes for
each person


Perform ear recognition or
1:1 verification


SUMMER RESEARCH


Ear
recognition is still a
relatively
new area
in biometrics
research
.



Potential
to be used in
real
-
world
applications to
identify/authenticate humans by their ears
.



Can be
used in both the low and
high security
applications and
in combination with
other biometrics
such as
face.

CONCLUSION


D. Hurley, B
Arbab
-
Zavar
, and M. Nixon
, The Ear as a Biometric
, In A. Jain, P.
Flynn, and A. Ross, Handbook of Biometrics, Chapter 7, Springer US, 131
-
150, 2007.


A. Jain, A. Ross, and S.
Prabhakar
.
An Introduction to Biometric Recognition
. In IEE
Trans. On Circuits and Systems for Video Technology, Jan. 2004.


R. N. Tobias,
A Survey of Ear as a Biometric: Methods, Applications, and Databases
for Ear Recognition
.


Carreira
-
Perpiñán
, M. Á. (1995):

Compression neural networks for feature extraction:
Application to human recognition from ear images

(in Spanish). MSc thesis, Faculty of
Informatics, Technical University of Madrid, Spain.


http
://
www.advancedsourcecode.com/earrecognition.asp


http://
vislab.ucr.edu/PUBLICATIONS/pubs/Chapters/2009/3D%20Ear%2
0Biometrics09.pdf


http://
www.security.iitk.ac.in/contents/publications/more/ear.pdf


http://
www.technovelgy.com/ct/Technology
-
Article.asp?ArtNum=98

REFERENCES