High confidence recognition of persons by iris patterns

Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in six field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statistical independence on iris phase structure encoded by multi-scale quadrature wavelets. The combinatorial complexity of this phase information across different persons spans about 244 degrees of freedom and generates a discrimination entropy of about 3.2 bits/mm/sup 2/ over the iris, enabling real-time decisions about personal identity with extremely high confidence. The high confidence levels are important because they allow very large databases to be searched exhaustively (one-to-many "identification mode") without making any false matches, despite so many chances. Biometrics lacking this property can only survive one-to-one ("verification") or few comparisons. The paper explains the algorithms for iris recognition, and presents the results of 2.3 million comparisons among eye images acquired in trials in Britain, the USA, and Japan.