A system for rapid and automatic identification of persons, with very high reliability and confidence levels. The iris of the eye is used an optical fingerprint, having a highly detailed pattern that is unique for each individual and stable over many years. Image analysis algorithms find the iris in a live video image of a person's face, and encode its texture into a compact signature, or "iris code." Iris texture is extracted from the image at multiple scales of analysis by a self-similar set of quadrature (2-D Gabor) bandpass filters defined in a dimensionless polar coordinate system. The sign of the projection of many different parts of the iris onto these multi-scale quadrature filters, determines each bit in an abstract (256-byte) iris code. The degrees-of-freedom in this code are based on the principle forms of variation in a population of irises studied. Because of the universal mathematical format and constant length of the iris codes, comparisons between them are readily implemented by the Exclusive-OR (XOR) logical operation. Pattern recognition is achieved by combining special signal processing methods with statistical decision theory, leading to a statistical test of independence based on a similarity metric (the Hamming distance) that is computed from the XOR of any two iris codes. This measure positively establishes, confirms, or disconfirms, the identity of any individual. It also generates an objective confidence level associated with any such identification decision.