Biometric.docx

Page | 1
Biometric Security System using Iris Recognition System
A Seminar Report Submitted in partial fulfillment for the award of Degree of Masters
of Computer Applications
Submitted By
Twenty Singh
(20MC39)
Under Supervision of
Asst. Prof. B.R Ambedkar
Department of Computer Science & Information Technology
Faculty of Engineering & Technology
Mahatma Jyotiba Phule Rohilkhand University, Bareilly
2022

Page | 2
Candidate’s Declaration
I hereby declared that seminar report titled “Biometric Security System using Iris Recognition
System” is prepared by me based on available literature and I have not submitted it anywhere else
for the award of any other degree or diploma.
Date: Twenty Singh (213109020046)
Certificate from Supervisor
I certify that the above statement made by the candidate is true to the best of my knowledge.
Date: Asst. Prof. B.R Ambedkar

Page | 3
Table of content
Candidate’s declaration
Table of Content
Abstract
1. Introduction
1.1 Biometric Technology
1.2 Human Iris
1.3 Iris Recognitionsystem
1.4 Steps to follow
2. Architecture
3. Working of Iris Technology
3.1 Image Acquisition
3.2 Preprocessing.
3.3 Image Analysis.
3.4 Image Recognition.
4. Recording of Identities
5. ProcessOverview
6. Pattern Matching
7. Advantage of Iris Technology
8. Disadvantage ofiris Technology
9. Application Iris System
10. Reallife Applications
11. Comparisonof Iris Technology with other
Biometric technology
12.Comparison
13. Conclusion
14. References
Page no.
2
3
4
5
5
5-6
6
7
7
7
7
8
10
11
11
12
12-13
14
14
15
15
16
17
17
18-20

Page | 4
Abstract
In a biometric system a person is identified automatically by processing the unique features that are posed
by the individual. Iris Recognition is regarded as the most reliable and accurate biometric identification
system available. In Iris Recognition a person is identified by the iris which is the part of eye using pattern
matching or image processing using concepts of neural networks. The aim is to identify a person in real
time, with high efficiency and accuracy by analyzing the random patterns visible within the iris if. The
major applications of this technology so far have been: substituting for passports (automated international
border crossing); aviation security and controlling access to restricted areas at airports; database access
and computer login. This report discusses the use of the iris-based biometric recognition. Biometric
recognition is the automated recognition of individuals based on the physiological and behavioral
characteristics. The recognition can be positive or negative. It highlights the key areas where the iris
biometric method has been used successfully, and what are its shortfalls. It presents an overview of the
algorithm used in Iris biometric recognition. It also compares the performance of the Iris biometric
method with the other biometric methods in terms of cost-effectiveness, usability, speed and other factors.

Page | 5
1 Introduction
1.1 Biometric Technology
Biometrics is the automated measurement of physiological or behavioral characteristics of individuals.
Physiological characteristics include face, fingerprints, iris and retinal features, hand geometry, and ears.
A biometric system provides automatic recognition of an individual based on some sort of unique feature
or characteristic possessed by the individual. Biometric systems have been developed based on
fingerprints, facial features, voice, hand geometry, handwriting, the retina [1], and the one presented in
this thesis, the iris. Behavioral characteristics include handwritten signature, voice, keystrokes, and gait
(how a person walks).
Today there are many uses of biometrics each has its own advantages and disadvantages according to the
requirements on biometric identifiers. A practical biometric system should have acceptable recognition
accuracy, speed with reasonable resource requirements. It should be harmless to users, be accepted by the
intended population, and be sufficiently robust to various fraudulent methods.
For a long time the fingerprints have been one of the most widely used and accepted biometric. This is
evidenced by the Chinese who have used fingerprints to sign documents for over 1000 years. Iris
recognition is one of the biometrics that is used for identification and verification due to its accuracy. In a
verification system, the system authenticates a person’s identity by comparing the captured biometric
characteristic with her own biometric template(s) prestored in the system. In an identification system, the
system recognizes an individual by searching the entire template database for a match.
1.2 Human Iris
The iris is a thin circular diaphragm, which lies between the cornea and the lens of the human eye. A
front-on view of the iris is shown in Figure 1.1. The iris is perforated close to its centre by a circular
aperture known as the pupil. The function of the iris is to control the amount of light entering through the
pupil, and this is done by the sphincter and the dilator muscles, which adjust the size of the pupil. The
average diameter of the iris is 12 mm, and the pupil size can vary from 10% to 80% of the iris diameter
[2]. The iris consists of a number of layers, the lowest is the epithelium layer, which contains dense
pigmentation cells. The stromal layer lies above the epithelium layer, and contains blood vessels, pigment
cells and the two iris muscles. The density of stromal pigmentation determines the colour of the iris. The

Page | 6
externally visible surface of the multi-layered iris contains two zones, which often differ in colour [3]. An
outer ciliary zone and an inner pupillary zone, and these two zones are divided by the collarette – which
appears as a zigzag pattern.
Fig 1.1 Front View of Human Eye
1.3 Iris Recognition system
 Iris recognition is fast developing to be a full proof and fast identification technique that canbe
administered cost effectively. It is a classic biometrics application that is in an advanced stage of
research all over the world.
 Iris cameras perform recognition detection of a person’s identity by mathematical analysis of the
random patterns that are visible within the iris of an eye from some distance. It combinescomputer
vision, pattern recognition, statistical inference and optics.

Page | 7
1.4 Steps to follow
 A person stands in front of the iris identification system, between one or three feet away, while a
wide angle camera calculates the position of their eye.
 A second camera zooms in on the eye and takes a black and white image.
 Once the iris is in focus, it overlays a circular grid on the image of the iris and identifies the light
and dark areas, like an “eye print”.
 To prevent a fake eye from being used to fool system, these devices may vary the light shine into
the eye and watch for pupil dilation.
2. Architecture
Operator Image
Acquisition
Iris
Localization
Image Digitizing
Image
Bar Codes
Stored in
Computer
Database
Pattern
Matching
Numeric
Code
Fig 1.2 Block Diagram of Iris Recognition
3. Working of Iris Technology
The iris identification program may be divided into four main functional blocks:
1.Image Acquisition.
2.Preprocessing.
3.Image Analysis.
4.Image Recognition.

Page | 8
3.1 Image Acquisition
Image Acquisition is the first step in any image processing system. The general aim of any image
acquisition is to transform an optical image (real-world data) into an array of numerical data which could
be later manipulated on a computer. Image acquisition is achieved by suitable cameras.
We use different cameras for different applications. If we need an X-ray image, we use a camera (film)
that is sensitive to X-rays. If we want an infrared image, we use cameras that are sensitive to infrared
radiation. For normal images (family pictures, etc.), we use cameras that are sensitive to the visual
spectrum.
 To acquire images with sufficient resolution and sharpness to support recognition.
 Good contrast and high illumination.
 Optics and Camera:
 Human heads are on the order of 15 cm wide.
 In case of a portal, we needed a capture volume width on the order of 20–30 cm.
 More than 200 pixels or more across the iris- Good quality.
 Of 150–200 pixels across the iris – Acceptable quality
 Of 100–150 pixels to be of- Marginal quality.
 Camera Distance up to 3 meters.
 High Quality Image, Daughman’s Algorithm expect minimum 640X480.

Page | 9
3.2 Preprocessing
The aim of pre-processing is to improve the quality of the image so that we can analyse it in a better way.
By preprocessing we can suppress undesired distortions and enhance some features which are necessary for
the particular application we are working for. Those features might vary for different applications.For
example, if we are working on a project which can automate Vehicle Identification, then our main focus
lies on the vehicle, its colour, the registration plate, etc., We do not focus on the road or the sky or
something which isn't necessary for this particular application.
 The acquired image always not only “useful” parts (IRIS), but also some “irrelevant” parts
e.g. eyelid, pupil.
 Preprocessing removes the effect of spots/holes lying on the papillary area.
 The Preprocessing module first transforms the true colour into intensity image
So the preprocessing is composed of two steps:
1. Iris Localization
 Both the inner boundary and the outer boundary of a typical iris can be taken as circles.
 But the two circles are usually not co-centric.
 The inner boundary between the pupil and the iris is detected.
 The outer boundary of the iris is more difficult to detect because of the low contrast between the
two sides of the boundary.
 The outer boundary is detected by maximizing changes of the perimeter- normalized along the
circle.

Page | 10
2. Edge Detection
Edge detection is a technique of image processing used to identify points in a digital image with
discontinuities, simply to say, sharp changes in the image brightness. These points where the image
brightness varies sharply are called the edges (or boundaries) of the image.
 It is used to find complex object boundaries by marking potential edge point corresponding to
places in an image where rapid change in brightness occurs.
 In other words, edge is defined by the discontinuity in gray values. An edge separates two
distinct objects.
Fig. 3 Edge Detection
3.3 Image Analysis
 The features of the iris are then analyzed and digitized into a 512 byte (4096 bits) Iris Code record.
 In this iris code half of the describes the features and another half of the describes the control the
comparison process.

Page | 11
3.4 Image Recognition
 Iris code record is stored in the database for future comparison.
 During a recognition attempt, when an iris is presented at a recognition point, the same process is
repeated ; however the resulting Iris Code record is not stored but is compared to every file in the
database.
4. Recording of Identities

Page | 12
5. ProcessOverview
6. PatternMatching
Pattern matching in computer vision refers to a set of computational techniques which enable
the localization of a template pattern in a sample image or signal. Such template pattern can be a specific
facial feature, an object of known characteristics or a speech pattern such as a word.
Many of the challenges in computer vision, signal processing. Speech recognition, speaker identification,
multimedia document recognition (MDR), automatic medical diagnosis. In a typical pattern recognition
application, the raw data is processed and converted into a form that is amenable for a machine to use.
Pattern recognition involves the classification and cluster of patterns.

Page | 13
 In classification, an appropriate class label is assigned to a pattern based on an abstraction that
is generated using a set of training patterns or domain knowledge. Classification is used in
supervised learning.
Clustering generated a partition of the data which helps decision making, the specific decision-making
activity of interest to us. Clustering is used in unsupervised learning.
 The produced code matches the encoded features stored in the database.
 One technique for comparing two Iris Codes is to use the Hamming distance, which is the number
of corresponding bits that differ between the two Iris Codes.

Page | 14
7. Advantage of Iris Technology
Features may be represented as continuous, discrete, or discrete binary variables. A feature is a
function of one or more measurements, computed so that it quantifies some significant characteristics
of the object.
 Uniqueness of iris patterns hence improved accuracy.
 Highly protected, internal organ of the eye.
 Stability : Persistence of iris patterns.
 Non-invasive : Relatively easy to be acquired.
 Unique - the probability of two rises producing the same code is nearly impossible.
 Flexible - iris recognition technology easily integrates into existing security systems or operates
as a standalone
 Patterns apparently stable throughout life.
 Reliable - a distinctive iris pattern is not susceptible to theft, loss or compromise
8. Disadvantage ofIris Technology
 Alcohol consumption causes deformation in Iris pattern
 Illumination should not be visible or bright
 Obscured by eyelashes, lenses, reflections
 It will be difficult to capture an image of handicap people sitting on wheel chair because the
cameras are usually attached on the wall and capture an image up to a certain height.
 The iris recognition systems are much costlier than other biometric technologies.
 If a person is wearing glasses or facing direct sunlight for quite a while, than it may affect the
authentication.

Page | 15
9. Application of Iris System
 Computer login: the iris as a living password.
 National border controls: the iris as a living passport.
 Driving licenses and personal certificates.
 Internet security, control of access to privileged information.
 Premises access control (Home, Office, Laboratory).
 Anti-terrorism (e.g. security screening at airports)
 Financial Transactions (electronic commerce and banking).
 Secure accesses to bank cash machine accounts.
 Credit-card authentication.
 Automobile ignition and unlocking; anti-theft devices
10 Reallife Applications
 Aadhaar India's Unique ID project for its one billion citizens uses Iris scan as one of the
identification features.
 United Arab Emirates uses it in border patrol.
 Permits passport free immigration in several countries like Netherlands, Canada, US.
 Google uses iris scanners to control access to their datacenters.

Page | 16
11 Comparison of Iris technologywith other biometric
 Accurate
 Stability
 Fast
 Scalable

Page | 17
12 Comparison
13 Conclusion
 The applications of iris recognition are rapidly growing in the field of security, due to it’s high rate
of accuracy. This technology has the potential to take over all other security techniques, as it
provides a hands-free, rapid and reliable identification process.
 Iris recognition has proven to be a very useful and versatile security measure.
 It is a quick and accurate way of identifying an individual with no chance for human error.
 Iris recognition is widely used in the transportation industry and can have many applications in
other fields where security is necessary.
 Iris recognition will prove to be a widely used security measure in the future.

Page | 18
14 References
[1] S. Sanderson, J. Erbetta. Authentication for secure environments based on iris scanning technology.
IEE Colloquium on Visual Biometrics, 2000.
[2] J. Daugman. How iris recognition works. Proceedings of 2002 International Conference on Image
Processing, Vol. 1, 2002.
[3] http://findbiometrics.com/solutions/iris-scanners-recognition/
[4] http://www.irisid.com/irisrecognitiontechnology
[5] http://www.slideshare.net/search/slideshow?searchfrom=header&q=iris+recognition
[6] http://en.wikipedia.org/wiki/Iris_recognition#History

Biometric.docx

More Related Content

Similar to Biometric.docx (20)

Recently uploaded (20)

Biometric.docx