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Iris Biometric Recognition for Person Identification in Security Systems
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ABSTRACT
The security is an important aspect in our daily life whichever
the system we consider security plays vital role. The biometric
person identification technique based on the pattern of the human
iris is well suited to be applied to access control and provides
strong e-security. Security systems having realized the value of
biometrics for two basic purposes: to verify or identify users. In
this paper we focus on an efficient methodology for
identification and verification for iris detection, even when the
images have obstructions, visual noise and different levels of
illuminations and we use the CASIA iris database it will also
work for UBIRIS Iris database which has images captured from
distance while moving a person. Efficiency is acquired from iris
detection and recognition when its performance evaluation is
accurate.
Keywords: Biometrics, Iris identification, occluded images,
UBIRIS Iris database.
1. INTRODUCTION
Today's e-security are in critical need of finding accurate, secure
and cost-effective alternatives to passwords and personal
identification numbers (PIN) as financial losses increase
dramatically year over year from computer-based fraud such as
computer hacking and identity theft [12]. Biometric solutions
address these fundamental problems, because an individual's
biometric data is unique and cannot be transferred.
Biometrics which refers to identifying an individual by his or
her physiological or behavioral characteristics has capability to
distinguish between authorized user and an imposter. An
advantage of using biometric authentication is that it cannot be
lost or forgotten, as the person has to be physically present
during at the point of identification process [9].Biometrics is
inherently more reliable and capable than traditional knowledge
based and token based techniques. The commonly used
biometric features include speech, fingerprint, face, Iris, voice,
hand geometry, retinal identification, and body odor
identification [10] as in Figure1
Figure1: Examples of Biometrics
To choose the right biometric to be highly fit for the particular
situation, one has to navigate through some complex vendor
products and keep an eye on future developments in technology
and standards. Here comes a list of Biometrics with
comparatives:
Facial Recognition: Facial recognition records the spatial
geometry of distinguishing features of the face. Different
vendors use different methods of facial recognition, however, all
focus on measures of key features of the face. Facial recognition
has been used in projects to identify card counters or other
undesirables in casinos, shoplifters in stores, criminals and
terrorists in urban areas. This biometric system can easily spoof
by the criminals or malicious intruders to fool recognition
system or program. Iris cannot be spoofed easily.
Palm Print: Palm print verification is a slightly modified form
of fingerprint technology. Palm print scanning uses an optical
reader very similar to that used for fingerprint scanning;
however, its size is much bigger, which is a limiting factor for
use in workstations or mobile devices.
Signature Verification: It is an automated method of examining
an individual’s signature. This technology is dynamic such as
speed, direction and pressure of writing, the time that the stylus
is in and out of contact with the ―paper‖. Signature verification
templates are typically 50 to 300 bytes. Disadvantages include
problems with long-term reliability, lack of accuracy and cost.
Fingerprint: A fingerprint as in Figure1 recognition system
constitutes of fingerprint acquiring device, minutia extractor and
minutia matcher. As it is more common biometric recognition
used in banking, military etc., but it has a maximum limitation
that it can be spoofed easily. Other limitations are caused by
particular usage factors such as wearing gloves, using cleaning
fluids and general user difficulty in scanning.
Iris Scan: Iris as shown in Figure2 is a biometric feature, found
to be reliable and accurate for authentication process
comparative to other biometric feature available today which is
as shown Table1 (a) (b).
As a result, the iris patterns in the left and right eyes are
different, and so scan be used quickly for both identification and
verification applications because of its large number of degrees
of freedom. Iris as in Figure 2 is like a diaphragm between the
pupil and the sclera and its function is to control the amount of
light entering through the pupil. Iris is composed of elastic
connective tissue such as trabecular meshwork. The
agglomeration of pigment is formed during the first year of life,
and pigmentation of the stroma occurs in the first few years
Vanaja Roselin.E.Chirchi
Ph.D. Research scholar
JNT University, Kukatpally,
Hyderabad- 500085. AP, India
Dr.L.M.Waghmare
Professor & Dean (R&D)
SGGS institute of Engineering &
Technology,
Vishnupuri, Nanded-431602, MS, India
E.R.Chirchi
Asst. Professor, CSE Dept
MBES COE. Ambajogai
BEED 431517, MS, India
International Journal of Computer Applications (0975 – 8887)
Volume 24– No.9, June 2011
2
[7][8]. The highly randomized appearance of the iris makes its
use as a biometric well recognized. Its suitability as an
exceptionally accurate biometric derives from [4]:
i.The difficulty of forging and using as an imposter person;
ii. It is intrinsic isolation and protection from the external
environment;
iii. It’s extremely data-rich physical structure.
Figure2: Structure of iris.
iv. Its genetic properties—no two eyes are the same. The
characteristic that is dependent on genetics is the pigmentation
of the iris, which determines its color and determines the gross
anatomy. Details of development, that are unique to each case,
determine the detailed morphology;
v.its stability over time; the impossibility of surgically modifying
it without unacceptable risk to vision and its physiological
response to light, which provides a natural test against artifice.
After the discovery of iris, John G. Daugman, a professor of
Cambridge University[8][9], suggested an image-processing
algorithm that can encode the iris pattern into 256 bytes based
on the Gabor transform.
In general, the iris recognition system is composed of the
following five steps as depicted in Figure 3 According to this
flow chart, preprocessing including image enhancement.
The remainder of the paper is organized as follows: Section (2)
focuses on Image Acquisition Section (3) emphasizes on
Preprocessing Section (4) focuses on Feature extraction
Section(5) emphasizes on Pattern matching Section(6)
emphasizes on identification and verification Section (7)
emphasizes on conclusion of the proposed Algorithm.
2.IMAGE ACQUISITION
An image of the eye to be analyzed must be acquired first in
digital form suitable for analysis. In further implementation we
will be using CASIA database [17]. The main focus CASIA
database is to minimize the requirement of user cooperation, i.e.,
the analysis and proposal of methods for the automatic
recognition of Individuals, using images of their iris captured ata-
distance and minimizing the required degree of cooperation
from the users, probably even in the covert mode [13].