Effect of Pupil Dilation and Constriction on the Distribution of Bit Errors within the Iris

Abstract

Texture information in the iris image is not uniform in discriminatory information content for biometric identity verification. The bits in an iris code obtained from the image differ in their consistency from one sample to another for the same identity. In this work, errors in bit strings are systematically analysed in order to investigate the effect of light-induced and drug-induced pupil dilation and constriction on the consistency of iris texture information. The statistics of bit errors are computed for client and impostor distributions as functions of radius and angle. Under normal conditions, a V-shaped radial trend of decreasing bit errors towards the central region of the iris is obtained for client matching, and it is observed that the distribution of errors as a function of angle is uniform. When iris images are affected by pupil dilation or constriction the radial distribution of bit errors is altered. A decreasing trend from the pupil outwards is observed for constriction, whereas a more uniform trend is observed for dilation. The main increase in bit errors occurs closer to the pupil in both cases.

A biomechanical approach to iris normalization

“…If the degree of dilation is different during enrollment and recognition, both dilation and constriction can affect the performance. Recently, Tomeo-Reyes and Chandran [17] performed a bit error analysis on the iris code to investigate the effect of light-and drug-induced pupil dilation and constriction on the consistency of texture information within the iris. Their results showed that bit errors increase by over 10% when comparing a 'normal' image with dilated or constricted images.…”

Understanding the subject-specific effects of pupil dilation on iris recognition in the NIR spectrum

“…Their results confirm with the works of [18] and [15] that the difference in pupil dilation remains evident in iris recognition algorithms. Furthermore, Tomeo-Reyes and Chandran [19] performed bit error analysis to explore the consistence of texture information of the iris region from various degrees of dilation. Their results showed an increase in bit errors by by over 10% when comparisons were made between extreme and intermediary pupil sizes.…”

“…Our motivation for this work comes from the observations of [15], [17] and [19] that the dilation differences between the acquired and enrolled iris images affect iris matching accuracy. Furthermore, pupil dilation levels are different for each individual and these variations need to be considered.…”

The states of dilation in iris recognition (a preliminary study)

“…In their work, existence and uniqueness conditions were developed and numerical simulations showed the efficacy of their approach. Later, from a template standpoint, Tomeo-Reyes and Chandran [10] performed bit error analysis to explore the consistency of iris texture information across various degrees of dilation. Their results showed that, when image comparisons are made between the extreme degrees of dilation 1 to the average dilation, bit errors increased by over 10%.…”

“…Our motivation for this work comes from the literature in [4], [9], [10] and [11] that suggest a need to develop an analytical and universal approach to describe the effects of dilation on iris recognition caused by ambient lighting. The works of [4] and [10] explore this concept from a template perspective; however, this is mainly from an empirical point of view, which is dependent on the technology and data at hand and does not fully consider the physiological effects of the pupil. Additionally, the development of the mathematical models in [9] and [11] illustrate that the iris muscle activity, governed by the sphincter and dilator muscles, determines changes in both pupil size and iris deformation.…”