3. ABSTRACT
The main purpose of this Technology is provide the high security. For
iris recognition first of all database will be created in MATLAB using
webcam. Then iris localization is done, after localization normalization
and segmentation will performed, for that hough transform algorithm
implemented. In last binarization of image is performed. Then binary
output is compared with database image’s binary value. From
comparison recognition is done, we can identify whether person is
authorized or not.Eye trackers are used in research on the visual
system, in psychology, marketing, as an input device for human-
computer interaction, and in product design. The most popular variant
uses video images (frames of images) from which the eye position is
extracted.
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4. EXISTINGTECHNOLOGY
Biometrics is the science and technology of measuring and analyzing
biological data. It refers to technologies that measure and analyze human
body
Characteristics.
FINGERPRINT TECHNOLOGY :
A Fingerprint is the feature pattern of one finger.
Each individual has unique fingerprints so the uniqueness of a
fingerprint is exclusively determined by local ridge characteristics
and their relationships.
It is the process of comparing known fingerprint against another
fingerprint to determine if the is authorised or not.
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6. PROPOSED SYSTEM
Characteristics of the iris make it very attractive for use as a biometric .
The unique iris pattern from a digitised image of the eye is encoded into a
biometric template , and then stored in database.
A Biometric template contains objective mathematical representation of
the unique information stored in the iris and allows comparisons between
templates.
John daugman patented and implemented a first working , automated iris
recognition system.
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8. WORKING METHODOLOGY
Image scanned using webcam
Data base created in matlab
Iris localization and segmentation using
hough transform
Sampling and binarization using
haarwavelet transform
Iris code comparision and identification
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9. ACQUISITION OF IMAGE
Iris localization :
Both the inner and outer boundary of a typical iris can be taken as
circles.
The inner boundary between the pupil and iris can be detected
The outer boundary of the iris is more difficult to detect .
The outer boundary can be detected by maximizing changes of the
parameters normalized along the circle.
Iris Normalization :
The size of the pupil may change due to the variation of the
illumination and the associated elastic deformation in the iris texture
may interface with the results of pattern matching
Since both the inner and outer boundaries of the iris have been
detected, it is easy to map the iris ring to rectangular block of texture
of a fixed size using hough transform.
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10. PatternMatching:
How closely 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.
In hamming distance 30% of the bits in two iris codes are allowed to
disagree due to imaging noise, reflections ,etc ., while still declaring
them to be match.
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11. ADVANTAGES
Highly protected , internal organ of the eye
Externally visible patterns imaged from a distance
Iris shape is far more predictable than that of the face
No need for a person to touch any equipment
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12. APPLICATIONS
ATMs
Computer login : The iris as a living password.
Credit –card authentication.
Secure financial transaction (e-commerce , banking)
Internet security, control of access to privileged information.
National Border Controls : The iris as a living password.
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13. FUTURE SCOPE
Improve Patient Care:
New , ambulatory patients will enroll in this iris
recognition database during admission. Previously enrolled patients will
be identify themselves at any of the networked scanning stations
throughout the facility. Non –ambulatory and emergency patients and
those who don’t know who they are , such as dementia patients will be
identified or enrolled without interrupting the critical time to treatment.
Keep Officers Safe On Street :
Officers will perform a quick iris scan to identify
individual from a distance, providing a critical layer of safety. Wireless ,
lightweight , and portable , the iris scanner is operated with one hand ,
leaving the other hand free for fast reaction.
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14. CONCLUSION
After understanding importance of Iris detection and localization stage
different detection techniques are implemented. For video frame pupil
detection circular Hough transform, histogram equalization and
thresholding are used. After measuring hamming distance iris of
authorized person is identified.
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15. REFERENCES
• K. Yiu-ming Cheung, Senior Member, IEEE, and Qinmu Peng,
• Member, IEEE “Eye Gaze Tracking With a Web Camera in a
Desktop Environment” IEEE TRANSACTIONS ON HUMAN-
MACHINE SYSTEMS, VOL. 45, NO. 4, AUGUST 2015.
• Tanvir Zaman Khan, Prajoy Podder and Md. Foisal Hossain “Fast
and Efficient Iris Segmentation Approach Based on Morphology and
Geometry Operation” vol.4 ,IEEE 2014.
• Yahya and M. Nordin, “A New Technique for Iris Localization”,
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