14-04-2014, 12:26 PM
BIOMETRIC TECHNOLOGY
[attachment=61267]
INTRODUCTION:
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 and the one presented in this thesis, the iris.
Biometric systems work by first capturing a sample of the feature, such
as recording a digital sound signal for voice recognition, or taking a digital colour image
for face recognition. The sample is then transformed using some sort of mathematical
function into a biometric template. The biometric template will provide a normalised,
efficient and highly discriminating representation of the feature, which can then be
objectively 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 an identification mode, where a template is created for an individual and
then a match is searched for in the database of pre-enrolled templates.
A good biometric is characterized by use of a feature that is; highly
unique, stable and be easily captured and the chance of any two people having the same
characteristic will be minimal. Also the feature does not change over time .In order to
provide convenience to the user, and prevent misrepresentation of the feature.
IRIS RECOGNITION SYSTEM:
The purpose of ‘Iris Recognition’, a biometrical based technology for
personal identification and verification, is to recognize a person from his/her iris prints.
In fact, iris patterns are characterized by high level of stability and distinctiveness. Each
individual has a unique iris.
The probability of finding two people with identical iris patterns is considered
to be approximately 1 in 1052(population of the earth is of the order 1010). Not even one-
egged twins or a future clone of a person will have the same iris patterns.It is stable over
time even though the person ages. Iris recognition is the most precise and fastest of the
biometric authentication methods.
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.
WORKING OF IRIS RECOGNITION SYSTEM:
Image processing techniques can be employed to extract the unique iris
pattern from a digitized image of the eye, and encode it into a biometric template, which
can be stored in a database. This biometric template contains an objective mathematical
representation of the unique information stored in the iris, and allows comparisons to be
made between templates. When a subject wishes to be identified by iris recognition
system, their eye is first photographed, and then a template created for their iris region.
This template is then compared with the other templates stored in a database until either a
matching template is found and the subject is identified, or no match is found and the
subject remains unidentified.
IRIS LOCALIZATION:
Before performing iris pattern matching, the boundaries of the iris should
be located. In other words, we are supposed to detect the part of the image that extends
from inside the limbus (the border between the sclera and the iris) to the outside of the
pupil. We start by determining the outer edge by first down sampling the images by a
factor of 4 then use the canny operator with the default threshold value given by Matlab,
to obtain the gradient image.
Since the picture was acquired using an infrared camera the pupil is a
very distinct black circle. The pupil is in fact so black relative to everything else in the
picture simple edge detection should be able to find its outside edge very easily.
Furthermore, the thresholding on the edge detection can be set very high as to ignore
smaller less contrasting edges while still being able to retrieve the entire perimeter of the
pupil. The best edge detection algorithm for outlining the pupil is canny edge detection.
This algorithm uses horizontal and vertical gradients in order to deduce edges in the
image. After running the canny edge detection on the image a circle is clearly present
along the pupil boundary.
[attachment=61267]
INTRODUCTION:
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 and the one presented in this thesis, the iris.
Biometric systems work by first capturing a sample of the feature, such
as recording a digital sound signal for voice recognition, or taking a digital colour image
for face recognition. The sample is then transformed using some sort of mathematical
function into a biometric template. The biometric template will provide a normalised,
efficient and highly discriminating representation of the feature, which can then be
objectively 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 an identification mode, where a template is created for an individual and
then a match is searched for in the database of pre-enrolled templates.
A good biometric is characterized by use of a feature that is; highly
unique, stable and be easily captured and the chance of any two people having the same
characteristic will be minimal. Also the feature does not change over time .In order to
provide convenience to the user, and prevent misrepresentation of the feature.
IRIS RECOGNITION SYSTEM:
The purpose of ‘Iris Recognition’, a biometrical based technology for
personal identification and verification, is to recognize a person from his/her iris prints.
In fact, iris patterns are characterized by high level of stability and distinctiveness. Each
individual has a unique iris.
The probability of finding two people with identical iris patterns is considered
to be approximately 1 in 1052(population of the earth is of the order 1010). Not even one-
egged twins or a future clone of a person will have the same iris patterns.It is stable over
time even though the person ages. Iris recognition is the most precise and fastest of the
biometric authentication methods.
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.
WORKING OF IRIS RECOGNITION SYSTEM:
Image processing techniques can be employed to extract the unique iris
pattern from a digitized image of the eye, and encode it into a biometric template, which
can be stored in a database. This biometric template contains an objective mathematical
representation of the unique information stored in the iris, and allows comparisons to be
made between templates. When a subject wishes to be identified by iris recognition
system, their eye is first photographed, and then a template created for their iris region.
This template is then compared with the other templates stored in a database until either a
matching template is found and the subject is identified, or no match is found and the
subject remains unidentified.
IRIS LOCALIZATION:
Before performing iris pattern matching, the boundaries of the iris should
be located. In other words, we are supposed to detect the part of the image that extends
from inside the limbus (the border between the sclera and the iris) to the outside of the
pupil. We start by determining the outer edge by first down sampling the images by a
factor of 4 then use the canny operator with the default threshold value given by Matlab,
to obtain the gradient image.
Since the picture was acquired using an infrared camera the pupil is a
very distinct black circle. The pupil is in fact so black relative to everything else in the
picture simple edge detection should be able to find its outside edge very easily.
Furthermore, the thresholding on the edge detection can be set very high as to ignore
smaller less contrasting edges while still being able to retrieve the entire perimeter of the
pupil. The best edge detection algorithm for outlining the pupil is canny edge detection.
This algorithm uses horizontal and vertical gradients in order to deduce edges in the
image. After running the canny edge detection on the image a circle is clearly present
along the pupil boundary.