introduction iris detection

7/29/2019 Introduction Iris detection

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Chapter 1 Introduction

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Chapter 1: Introduction

1.1 Biometrics

History of identification of humans is as old as human beings. With the development in

science and technology in the today’s modern world, human activities and transactions

have been growing tremendously. Authenticity of users has become an inseparable part

of all transactions involving human computer interaction. Most conventional modes of

authentication are based on knowledge based systems i.e. “what we know” (e.g.

passwords, PIN code etc) and / or token based systems i.e. “what we have” (e.g. ID cards,

passports, driving license etc.)[1]. Biometrics bring in stronger authentication capabilities

by adding a third factor, “who we are” based on our inherent physiological or behavioral

characteristics. The term "biometrics" is derived from the Greek words bio (life) and

metric (to measure). In other words, bio means living creature and metrics means the

ability to measure an object quantitatively [2]. The use of biometrics has been traced back

as far as the Egyptians, who measured people to identify them. Biometric technologies

are hence becoming the foundation of an extensive array of highly protected

identification and personal verification systems.

Biometrics is the branch of science which deals in automated methods of recognizing a

person based on a physiological or behavioral characteristic. This technology involves in

capturing and processing an image of a unique feature of an individual and comparing it

with a processed image captured previously from the database. The behavioral

characteristics are voice, odor, signature, gait, and voice whereas physiological

characteristics are face, fingerprint, hand geometry, ear, retina, palm prints and iris. All

biometric identification systems rely on forms of random variation among persons based

on these characteristics. More complex is the randomness, the more unique features for

identification; because more dimensions of independent variation produce code having

greater uniqueness.

Every biometric system has the following layout. First, it captures a sample of the

feature, such as recording a digital sound signal for voice recognition, or taking a digital

color image for face recognition or iris recognition, or retina scan for retina recognition.




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The sample is then transformed using some sort of mathematical function into a

biometric template. The biometric template will provide a normalized, efficient and

highly discriminating representation of the features, which then can be compared with

other templates in order to determine identity.

Most biometric systems allow two modes of operation. An enrolment mode for adding

templates to a database, and matching mode, where a template is created for an individual

and then a match is searched for in the database of pre-enrolled templates in two ways.

One is called “verification” in which one-to-one comparison is carried out and other is

“identification” in which one template is compared throughout the database.

If any physiological part has the following properties then it would be considered as a

biometric [3].

1.1.1 Properties for a Biometric

• Universality

Each person should have the characteristic.

• Distinctiveness

Any two persons should be sufficiently different in terms of the characteristic.

• Permanence

The characteristic should be sufficiently invariant (with respect to the matchingcriterion) over a period of time.

• Collect-ability

The characteristic can be measured quantitatively.

• User-friendliness

People must be willing to accept the system, the scanning procedure does not

have to be intrusive and the whole system should be easy to use.

• Accuracy

Accuracy of the system must be high enough, there must be a balance between

FAR (False Accept Rate) and FRR (False Reject Rate) depending upon the use of

the system.




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However, in a biometric system these should be practically implemented [4]. In addition

to that, there are number of other issues that should be considered, such as:

• Performance: It refers to the achievable recognition accuracy and speed, the

resources required to achieve the desired recognition accuracy and speed, as well

as the operational and environmental factors that affect the accuracy and speed.

• Acceptability: It indicates the extent to which people are willing to accept the use

of a particular biometric identifier (characteristic) in their daily lives.

• Circumvention: It reflects how easily the system can be fooled using fraudulent

methods.

• Cost: It is always a concern. In this case, the life-cycle cost of system

maintenance must also be taken into account.

1.2 Some Biometrics

Based on some basic definitions of biometrics as illustrated above, this section will give a

brief description of different biometric systems [5] as elaborated below.

1.2.1 Face Recognition

Face recognition is one of the most active research areas in computer

vision and pattern recognition [6-14]. A wide range of applicationsthat includes forensic identification, access control, face-based video

indexing and browsing engines, biometric identity authentication,

human-computer interaction and multimedia monitoring/surveillance.

The task of a face recognition system is to compare an input face image against a

database containing a set of face samples with known identity [15-22]. Facial recognition

has had some shortcomings, especially when trying to identify individuals in different

environmental settings (such as changes in lighting, changes in the physical, facial

features of people, such as new scars, beard etc.).

1.2.2 Fingerprint

Fingerprint imaging technology has been in existence for centuries. The use of

fingerprints as a unique human identifier starts back in second century B.C. in China,




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where the identity of the sender of an important document could be verified by his

fingerprint impression in the wax seal.

Fingerprint imaging technology looks to capture or read the

unique pattern of lines on the tip of one's finger. These unique

patterns of lines can either be in a loop, whorl or arch pattern.

The most common method involves recording and comparing

the fingerprint's “minutiae points”. Minutiae points can be

considered the uniqueness of an individual's fingerprint [23]. In

a typical fingerprint [24] that has been scanned by a fingerprint

identification system, there are generally between 30 and 40 minutiae. The research in

fingerprint identification technology has improved the identification rate to greater than

98 percent and a false positive (false reject) rate to smaller than one percent within the

Automated Fingerprint Identification System (AFIS) criminal justice program.

1.2.3 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 with the passage of time the shape of the

person's hand does not significantly change [25]. The basic

principle of operation behind the use of hand geometry is to

measure or record the physical geometric characteristics of an individual's hand. From

these measurements, a profile is constructed that can be used to compare against

subsequent hand readings by the user [26].

There are many benefits to use hand geometry as a solution to general security issues

including speed of operation, reliability, accuracy, small template size, ease of integration

into an existing system, and user-friendliness. Now, there are thousands of locations all

over the world that use hand geometry devices for access control and security purposes.

1.2.4 Retina

Retinal biometric involves analyzing the layer of blood vessels situated at the back of the

eye. Retinal scans involve a low-intensity infrared light that is projected through the back




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of the eye and onto the retina. Infrared light is used based on the fact that the blood

vessels on the retina absorb the infrared light faster than surrounding eye tissues. The

infrared light with the retinal pattern is reflected back to a video camera.

The video camera captures the retinal pattern and converts it into

data that is 35 elements in size [27]. This is not particularly

convenient if you are wearing glasses or concerned about having

close contact with the reading device. For these reasons, retinal

scanning is not warmly accepted by all users, although the

technology itself can work well. The current hurdle for retinal identification is the

acceptance by the users. Retinal identification has several disadvantages including

susceptible to disease damage (i.e. cataracts), viewed as intrusive and not very user

friendly, high amount of both user and operator skill required.

1.2.5 Signature Verification

Signatures are analyzed in the way a user signs his / her name.

Signing features include speed, velocity and pressure on writing

material. These features are as important as the finished

signature's static shape [28-31]. Signature verification enjoys a

synergy with existing processes that other biometrics do not. People are used to

signatures as a means of transaction-related identity verification and most would see

nothing unusual in extending this to encompass biometrics. Surprisingly, relatively few

significant signature applications have emerged compared with other biometric

methodologies.

1.2.6 Voice Authentication

Despite the inherent technological challenges, voice

recognition technology’s most popular applications will likely

provide access to secure data over telephone lines. Voice

biometrics has potential for growth because it requires no new

hardware. However, poor quality and surrounding noise can affect verification process. In

addition, the enrollment procedure is more complicated than other biometrics being not




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user-friendly. Speaker recognition systems [32] fall into two basic types: text-dependent

and text-independent. In text-dependent recognition, the speaker says a predetermined

phrase. This technique inherently enhances recognition performance, but requires a

cooperative user. In text independent recognition, the speaker neither says a

predetermined phrase nor cooperates or even not to be aware of the recognition system.

Speaker recognition suffers from several limitations. Different people can have similar

voices [33-35], and anybody’s voice can vary over time because of changes in health,

emotional state and age. Furthermore, variation in handsets or in the quality of a

telephone connection complicates the recognition process.

1.2.7 Gait Recognition

Gait recognition is relatively a new field in biometrics. A unique

advantage of gait as a biometric is that it offers potential for

recognition at a distance or at low resolution when other biometrics

might not be perceivable [36-41]. Recognition can be based on the

(static) human shape as well as walking, suggesting a richer recognition cue. Further, gait

can be used when other biometrics are obscured. It is difficult to conceal and/or disguise

motion as this generally impedes movement.

1.2.8 Ear Recognition

Ear recognition is carried out by three different methods: (i) taking a

photo of an ear, (ii) taking “earmarks” by pushing ear against a flat

glass and (iii) taking thermogram pictures of the ear [42-45]. The most

interesting parts of the ear are the outer ear and ear lope, but the whole

ear structure and shape is used [46]. Taking photo of the ear is the most commonly used

method in research. The photo is taken and it is combined with previous taken photos for

identifying a person. Ear database is publicly available via internet [47].

1.2.9 Iris Recognition

Iris recognition is a method of biometric authentication that uses pattern recognition

techniques based on images of the irises of an individual's eyes [1, 48-64]. Iris




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recognition uses camera technology and subtle IR illumination to reduce specular

reflection from the convex cornea to create images of the detail-rich

intricate structures of the iris. These unique structures are converted

into digital templates. They provide mathematical representations of

the iris that yield unambiguous positive identification of an

individual.

Iris recognition efficacy is rarely impeded by glasses or contact lenses. Iris technology

has the smallest outlier (those who cannot use/enroll) group of all biometric technologies.

The only biometric authentication technology has been designed for use in a one-to-many

search environment. A key advantage of iris recognition is its stability or template

longevity as barring trauma and a single enrollment can last a lifetime [65].

Among the physiological characteristics, iris is the best biometric. It has all the

capabilities of a good biometric.

1.3 Location of Iris in Human Eye

Iris is the colored part of eye which is visible when eye is open. If we observe an eye

image then blackish round shaped part is pupil. Iris is the only internal organ which can

be seen externally. Iris can be seen around the pupil and inside sclera, as shown in Figure

1.1.

Figure 1.1: Location of Iris




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1.3.1 Color of the eye

The iris gives color to the eye which depends on the amount of pigment present. If the

pigment is dense, the iris is brown. If there is a little pigment, the iris is blue. In some

cases, there is no pigment at all. So, the eye is light. Different pigments color eyes invarious ways to create the eye colors such as gray, green, etc. In bright light, the iris

muscles constrict the pupil thereby reducing the amount of light entering the eye.

Conversely, the pupil enlarges in dim light in order to allow greater amount of light to

enter in retina. Some irises with different colors are shown in Figure 1.2 [66].

Figure 1.2: Different colors of Iris

1.3.2 Working of the Eye

Light passes through the front structures of the eye (i.e. the cornea, lens and so forth).

These structures focus the light on the retina, a layer of light receptors at the back of the

eye. These receptors translate the image into a neural message which travels to the brain

via the optic nerve [67].

Light passes through a layer of transparent tissues at the front of the eye called the

cornea. The cornea bends the light and it is the first element in the eye's focusing system.

The light then passes through the anterior chamber, a fluid-filled space just behind the

cornea. This fluid is called the aqueous humor and it is produced by a gland called the

ciliary body. The light then passes through the pupil. The iris is a ring of pigmented




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muscular tissue that controls the size of the pupil. It regulates how much light enters the

eye - the pupil grows larger in dim light and shrinks to a smaller hole in bright light. The

light passes through the lens that helps focus the light from the pupil onto the retina.

Light from the lens passes through the vitreous body which is a clear jelly-like substance

that fills the back part of the eyeball. It is focused onto the retina that is a layer of light-

sensitive tissue at the back of the eye. The retina contains light-sensitive cells called

photoreceptors. It translates the light energy into electrical signals. These electrical

signals travel to the brain via the optic nerve. The retina is nourished by the choroids (a

highly vascularized membrane that exists just behind the retina). Aside from the

transparent cornea at the front of the eye, the eyeball is encased by a tough, white and

opaque membrane called the sclera [68].

Figure 1.3: Structure of the eye

1.3.2 Anatomy and Structure of Iris

The iris is a circular and adjustable diaphragm with the pupil. It is located in the chamber

behind the cornea. The iris is the extension of a large and smooth muscle which alsoconnects to the lens via a number of suspensor ligaments. These muscles expand and

contract to change the shape of the lens and to adjust the focus of images onto the retina

[26]. A thin membrane beyond the lens provides a light-tight environment inside the eye.

Thus, preventing stray light from confusing or interfering with visual images on the

retina. This is extremely important for clear high-contrast vision with good resolution or




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definition. The most frontal chamber of the eye, immediately behind the cornea and in

front of the iris, contains a clear watery fluid that facilitates good vision. It helps to

maintain eye shape, regulates the intra-ocular pressure, provides support for the internal

structures, supplies nutrients to the lens and cornea and disposes off the eye's metabolic

waste. The rear chamber of the front cavity lies behind the iris and in front of the lens. It

helps provide optical correction for the image on the retina. Some recent optical designs

also use coupling fluids for increased efficiency and better correction.

1.4 Research on Iris Recognit ion

Apparently, the first use of iris recognition as a basis for personal identification goes back

to efforts to distinguish inmates in the Parisian Penal System by visually inspecting their

irises, especially the patterning of color. In 1936, ophthalmologist Frank Burch proposed

the concept of using iris patterns as a method to recognize an individual [69]. By the

1980s, the idea had appeared in James Bond films but it still remained in science fiction

and conjecture [70]. In 1985, Leonard Flom and Aran Safir, ophthalmologists, proposed

the concept that no two irises are alike and were awarded a patent for the iris

identification concept in 1987 [63]. Flom approached John Daugman to develop an

algorithm to automate identification of the human iris. In 1993, the Defense Nuclear

Agency began work to test and deliver a prototype unit which was successfullycompleted by 1995 with their combined efforts. In 1994 [64], Daugman was awarded a

patent for his automated iris recognition algorithms.

1.5 Iris Recognit ion System

The iris recognition system consists of an automatic segmentation system that is based on

the edge detector and is able to localize the circular iris and pupil region, occluding

eyelids, eyelashes and reflections. The extracted iris region is then normalized into a

rectangular block with constant dimensions to account for imaging inconsistencies.

Features are extracted with different feature extraction methods to encode the unique

pattern of the iris into biometric template. The Hamming distance was employed for

classification of iris templates and two templates were found to match if hamming

distance is grater than a specific threshold.

introduction iris detection

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