Iris recognition is the process of recognizing a person by analyzing the apparent pattern of his
or her iris. There is a strong scientific demand for the proliferation of systems, concepts and
algorithms for iris recognition and identification. This is mostly because of the comparatively
short time that iris recognition systems have been around. In coparison to face, fingerprint
and other biometric traits there is still a great need for substantial mathematical and computervision
research and insight into iris recognition. One evidence for this is the total lack of publicly
available adequate datasets of iris images.
The program converts a photo of an eye to an 'unrolled' depiction of the subject's iris and
matches the eye to the agent's memory. If a match is found, it outputs a best match. The
current functionality matches that proposed in the original requirements.
A biometric system is essentially a pattern recognition system that operates by acquiring
biometric data from an individual, extracting a feature vector from the acquired data,
comparing this feature vector from the database feature vector. Person authentication has
always been an attractive goal in computer vision. Authentication systems based on human
characteristics such as face, finger, iris and voice are known Biometrics systems. The basis of
every biometric system is to get the input image and generate prominent feature vectors like
color, texture, etc.
Existing Biometric Technology
• Fingerprint Recognition
• Voice Recognition
• Signature Recognition
• Face Recognition
• Palm Recognition
Our Proposed Iris Recognition
Iris recognition is the most powerful biometric technology there is. Nothing else comes close.
• Interoperable cameras
An iris recognition camera takes a black and white picture from 5 to 24 inches away, depending
on the type of camera. The camera uses non-invasive, near-infrared illumination (similar to a
TV remote control) that is barely visible and very safe. Proof Positive certified cameras are in
compliance with all applicable international illumination safety standards, including ANSI/IESNA
RP-27.1-96 and IEC 60825-1 Amend.2, Class 1 LED. These are the latest worldwide standards.
In less than a few seconds, even on a database of millions of records, the Iris Code template
generated from a live image is compared to previously enrolled ones to see if it matches any of
them. The decision threshold is automatically adjusted for the size of the search database to
ensure that no false matches occur even when huge numbers of Iris Code templates are being
compared with the live one.
Some of the bits in an Iris Code template signify if some data is corrupted (for example by
reflections, or contact lens boundaries), so that it does not influence the process, and only valid
data is compared. Decision thresholds take account of the amount of visible iris data, and the
matching operation compensates for any tilt of the iris.
A key advantage of iris recognition is its ability to perform identification using a one-to-all
search of a database, with no limitation on the number of Iris Code records and no requirement
for a user first to claim an identity, for example with a card.
Hard disk : 40 GB
RAM : 256 MB
Processor : Pentium IV Processor
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