Introduction
Identity; It is the definition of who we are. Even today, identities are being confirmed by two methods:1. What we have
2. What we know
What we have is comprised of cards or documents such as CNICs (computerized national identity cards), driver licenses, passports or bay-form / birth certificates.
What we know typically consists of P/Ws (passwords) or PINs (personal identification numbers).
But as documents get counterfeited, passports are stolen and passwords are forgotten, we can no longer recognize/verify/authenticate an individual’s identity with any accuracy. And as a result, security of our restricted areas such as air/sea ports, buildings, finances and more is compromised.
To solve this challenge, identities are more frequently confirmed by a third party/component: who we are. We measure who we are in terms of biometrics, digital representations of our faces, finger-patterns, irises, retinas, palms, voice patterns, signatures – the list goes on.
Today, biometrics are the most accurate and secure representation of whom we truly are and can best keep others from stealing, misrepresenting or creating false identities.
SIS Iris Recognition Technology
Soft Innoavtive Solutions (SIS) Iris recognition technology is based on the distinctly colored ring surrounding the pupil of the eye. Made from elastic connective tissue, the iris is a very rich source of biometric data, having approximately 266 distinctive characteristics. These include the trabicular meshwork, a tissue that gives the appearance of dividing the iris radially, with striations, rings, furrows, a corona, and freckles. Iris recognition technology uses about 173 of these distinctive characteristics. Formed during the 8 months of gestation, these characteristics reportedly remain stable throughout a human’s lifetime, except in cases of injury. Iris recognition can be used in verification, identification and authentication systems. Iris recognition systems use a small, high-quality camera to capture a high-resolution image of the iris. The systems then define the boundaries of the iris, establish a coordinate system over the iris, and define the zones for analysis within the coordinate system.
Iris patterns become interesting as an alternative approach to reliable visual recognition of humans when imaging can be done at distances of less than a meter, and especially when there is a need to search very large databases without incurring any false matches despite a huge number of possibilities. Although small (11 mm) and sometimes problematic to image, the iris has the great mathematical advantage that its pattern variability among different persons is enormous. In addition, as an internal (yet externally visible) organ of the eye, the iris is well protected from the environment and stable over time. As a planar object its image is relatively insensitive to angle of illumination, and changes in viewing angle cause only affine transformations; even the non affine pattern distortion caused by pupillary dilation is readily reversible. Finally, the ease of localizing eyes in faces, and the distinctive annular shape of the iris, facilitates reliable and precise isolation of this feature and the creation of a size-invariant representation.
Soft Innoavtive Solutions (SIS) Iris recognition technology is based on the distinctly colored ring surrounding the pupil of the eye. Made from elastic connective tissue, the iris is a very rich source of biometric data, having approximately 266 distinctive characteristics. These include the trabicular meshwork, a tissue that gives the appearance of dividing the iris radially, with striations, rings, furrows, a corona, and freckles. Iris recognition technology uses about 173 of these distinctive characteristics. Formed during the 8 months of gestation, these characteristics reportedly remain stable throughout a human’s lifetime, except in cases of injury. Iris recognition can be used in verification, identification and authentication systems. Iris recognition systems use a small, high-quality camera to capture a high-resolution image of the iris. The systems then define the boundaries of the iris, establish a coordinate system over the iris, and define the zones for analysis within the coordinate system.
Iris patterns become interesting as an alternative approach to reliable visual recognition of humans when imaging can be done at distances of less than a meter, and especially when there is a need to search very large databases without incurring any false matches despite a huge number of possibilities. Although small (11 mm) and sometimes problematic to image, the iris has the great mathematical advantage that its pattern variability among different persons is enormous. In addition, as an internal (yet externally visible) organ of the eye, the iris is well protected from the environment and stable over time. As a planar object its image is relatively insensitive to angle of illumination, and changes in viewing angle cause only affine transformations; even the non affine pattern distortion caused by pupillary dilation is readily reversible. Finally, the ease of localizing eyes in faces, and the distinctive annular shape of the iris, facilitates reliable and precise isolation of this feature and the creation of a size-invariant representation.
