A Novel on understanding How IRIS Recognition works
V. M. Shinde, Prakash Singh Tanwar · 2014
Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in six field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statistical independence on iris phase structure encoded by multi-scale quadrature wavelets. The combinatorial complexity of this phase information across different persons spans about 249 degrees of freedom and generates a discrimination entropy of about 3.2 bits/mm2 over the iris, enabling real-time decisions about personal identity with extremely high confidence. The high confidence levels are important because they allow very large databases to be searched exhaustively (one-to-many .identification mode.) without making false matches, despite so many chances. Biometrics that lack this property can only survive one-to-one (.verification.) or few comparisons. This paper explains the iris recognition algorithms, and presents results of 9.1 million comparisons among eye images from trials in Britain, the USA, Japan, and Korea. Biometrics technology using advanced computer techniques is now widely adopted as a front-line security measure for both identity verification and crime detection, and also offers an effective crime deterrent. Biometric techniques are used for the purpose of identifying individual by using unique characteristics of each person deterrent. A term derived from ancient Greek: 'bios' meaning 'life' and 'metric', 'to measure'. A biometric system can operate in two modes. One is Verification (authentication) which refers to the problem of confirming or denying a person's claimed identity (Am I who I claim I am?). Second is Identification (Who am I?) which refers to the problem of establishing a subject's identity - either from a set of already known identities (closed identification problem) or otherwise (open identification problem). The human iris (Figure 1) is rich in features which can be used to quantitatively and positively distinguish one eye from another. The iris contains many collagenous fibers, contraction furrows, coronas, crypts, color, serpentine vasculature, striations, freckles, rifts, and pits. Measuring the patterns of these features and their spatial relationships to each other provides other quantifiable parameters useful to the identification process. In practical terms, statistical analyses indicate that the Iridium Technologies IRT process uses 240 degrees-of-freedom (DOF), or independent measures of variation to distinguish one iris from another.