Published on Sep 03, 2020
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 comparison 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