...................  ......

Introduction

Reliable automatic recognition of persons has long been an attractive goal. As in all pattern recognition problems, the key issue is the relation between inter-class and intra-class variability: objects can be reliably classified only if the variability among different instances of a given class is less than the variability between different classes. For example, in face recognition, difficulties arise from the fact that the face is a changeable social organ displaying a variety of expressions, as well as being an active three-dimensional (3-D) object whose image varies with viewing angle, pose, illumination, accoutrements, and age. It has been shown that, for “mug shot” images taken at least one year apart, even the best current algorithms can have error rates of 43%–50%. Against this intra-class (same face) variability, inter-class variability is limited because different faces possess the same basic set of features, in the same canonical geometry.

For all of these reasons, iris patterns become interesting as an alternative approach to reliable visual recognition of persons 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 nonaffine 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, facilitate reliable and precise isolation of this feature and the creation of a size-invariant representation. The iris begins to form in the third month of gestation and the structures creating its pattern are largely complete by the eighth month, although pigment accretion can continue into the first postnatal years. Its complex pattern can contain many distinctive features such as arching ligaments, furrows, ridges, crypts, rings, corona, freckles, and a zigzag collarette. Iris color is determined mainly by the density of melanin pigment in its anterior layer and stroma, with blue irises resulting from an absence of pigment: long-wavelength light penetrates while shorter wavelengths are scattered by the stroma. The striated trabecular meshwork of elastic pectinate ligament creates the predominant texture under visible light, whereas in the near-infrared (NIR) wavelengths used for unobtrusive imaging at distances of up to 1 m deeper and somewhat more slowly modulated stromal features dominate the iris pattern. In NIRwavelengths, even darkly pigmented irises reveal rich and complex features.

How Iris Recognition Works - John Daugman, PhD, OBE, University of Cambridge