Predicting Eye Color from Near Infrared Iris Images

Abstract

Iris recognition systems typically acquire images of the iris in the near-infrared (NIR) spectrum rather than the visible spectrum. The use of NIR imaging facilitates the extraction of texture even from darker color irides (e.g., brown eyes). While NIR sensors reveal the textural details of the iris, the pigmentation and color details that are normally observed in the visible spectrum are subdued. In this work, we develop a method to predict the color of the iris from NIR images. In particular, we demonstrate that it is possible to distinguish between light-colored irides (blue, green, hazel) and dark-colored irides (brown) in the NIR spectrum by using the BSIF texture descriptor. Experiments on the BioCOP 2009 dataset containing over 43,000 iris images indicate that it is possible to distinguish between these two categories of eye color with an accuracy of 90%. This suggests that the structure and texture of the iris as manifested in 2D NIR iris images divulges information about the pigmentation and color of the iris.