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Transcript of IRIS RECOGNITION
İPEK ŞAHBAZLAR CONTENTS INTRODUCTION
IRIS RECOGNITION TECHNOLOGY
IRIS RECOGNITION SYSTEM
BUDGET INTRODUCTION something you have (such as acard or token) something you are (biometric). Passwords are weak and easily crackable Security for systems is becoming more important Authentication plays a major role as a first line of defence against intruders
something you know (such as a password) Our project produces a working prototype program that functions as an Iris Recognition tool using the algorithms described by Professor John Dougman. The three main types of authentication:
token or card is recognisable The most common physical characteristics explored and used are facial features, eyes (iris and retina), fingerprints and hand geometry BIOMETRICS BIOMETRIC SYSTEM PROCESS WHAT IS BIOMETRICS Biometrics explores ways to distinguish between individuals using
personal traits Face Recognition has
problems with false rejection when
when people change their hair style
grow or shave a beard or wear glasses
Also it can not identify twins WHY WE CHOOSE IRIS RECOGNITION? Reasons •Iris recognition is regarded as the most reliable and accurate biometric identification system available. •All over the world people have unique iris because of the anatomical structure of an iris. •During the development of the iris, there is no genetic influence on it, a process known as “chaotic morphogenesis” that occurs during the seventh month of gestation, which means that even identical twins have differing irises. •The probability that two irises could produce exactly the same Iris Code is approximately 1 in 10 78. (The population of the earth is around 10 10.) •Iris is the only organ that not change during life period. It is not use after people dies because it quiescent in 3 seconds. Due to cultural issues, iris detection is suitable for use in places where other parts of the body, such as fingerprint or faces are not shown. STRUCTURE OF AN IRIS HISTORY OF IRIS RECOGNITION SYSTEM The idea of using iris patterns for personal
identification was originally proposed in 1936 by ophthalmologist Frank Burch, MD. John Daugman, who was teaching at Harvard University and now at
Cambridge University, to develop actual algorithms for iris recognition These algorithms, which Daugman developed in 1994, are the basis for all current iris recognition systems. AREAS OF USAGE COMPUTING ENVIRONMENT healthcare applications for medical records protection physical security to data centres or computer rooms In the areas of e-commerce ATMs are a major area where iris recognition is being trialled DISADVANTAGES •Small target (1 cm) to acquire from a distance (1 m)
•Moving target ...within another... on yet another
•Located behind a curved, wet, reflecting surface
•Obscured by eyelashes, lenses, reflections
•Partially occluded by eyelids, often drooping
•Deforms non-elastically as pupil changes size
•Illumination should not be visible or bright
•Some negative (Orwellian) connotations ADVANTAGES •Iris is a highly protected, internal organ of the eye.
•It is externally visible; patterns imaged from a distance.
•Iris patterns possess a high degree of randomness. Its variability: 244 degrees-of-freedom; its entropy: 3.2 bits per square millimeter; its uniqueness: set by combinatorial complexity.
•Changing pupil size confirms natural physiology
•Pre-natal morphogenesis (7th month of gestation)
•Iris patterns have limited genetic penetrance
•Iris patterns are apparently stable throughout life
•Encoding and decision-making are tractable WORKFLOW OF THE PROPOSED METHOD Steps of Human iris identification
1. Capturing the image
2. Defining the location of the iris and optimizing the image.
3. Normalization of an iris.
4. Feature extraction
5. Storing and matching the image. a. Original image
b. Localized image
c. Normalized image
d. Estimated local average intensity
e. Enhanced image CAPTURING THE IMAGE
The image of the iris can be captured using a standard camera using both visible and infrared light and may be either a manual or automated procedure Defining the Location of the Iris and Optimizing the Image
Once the camera has located the eye, the iris recognition system then identifies the image that has the best focus and clarity of the iris.
The image is then analyzed to identify the outer boundary of the iris where it meets the white sclera of the eye, the pupillary boundary and the centre of the pupil.
This results in the precise location of the circular iris. Detection of Inner Boundary
Inner boundary of iris is detected by detecting pupil.
First the gray scale input image is changed to binary format by using a suitable tight threshold.
Assuming that circular area of pupil is the largest black circular part, pupils detected by searching for largest black circular part in binary image.
Detection of Outer Boundary
The outer boundaries of iris are detected with the help of center of pupil