Iriscodes

Iriscodes, or IrisCodes, are binary representations of iris texture used in biometric identification. They encode distinctive patterns in the human iris into compact bit strings that allow fast numeric comparison. The concept was popularized by John Daugman in the 1990s as part of iris recognition research and has since become a standard in many biometric systems.

Generation of an iricode involves several steps. First, the iris region is located and segmented to separate it from the sclera, pupil, eyelids, and eyelashes. The segmented iris is then normalized to a fixed, rectangular dimension using a rubber-sheet model to compensate for pupil dilation and gaze. The normalized iris is processed with a bank of Gabor wavelets to extract local phase information; the sign of the filter responses at each position is quantized to create a binary code. An accompanying occlusion mask marks unreliable bits caused by eyelids, reflections, or noise, ensuring those bits are ignored during matching.

Matching between two iriscodes is performed with the Hamming distance, typically computed only over the overlapping, valid bits. A lower Hamming distance indicates higher similarity, and a system-specific threshold determines whether a pair is accepted as a match. The method is valued for its discriminative power, computational efficiency, and suitability for large-scale databases.

Limitations include dependence on high-quality iris images and accurate segmentation; occlusions, reflections, or off-angle captures can degrade performance. Privacy considerations center on the handling of biometric data and the need for safeguards against spoofing and unauthorized cross-referencing. Variants and refinements continue to appear in research and commercial deployments to improve robustness and privacy.