High confidence recognition of persons by rapid video analysis of iris texture

Abstract

A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person's face is the detailed texture of each eye's iris: an estimate of its statistical complexity in a sample of the human population reveals variation corresponding to several hundred independent degrees of freedom. Morphogenetic randomness in the texture expressed phenotypically in the trabecular meshwork ensures that a test of statistical independence on two coded patterns originating from different eyes is passed almost certainly, whereas the same test is failed almost certainly when the compared codes originate from the same eye. The visible texture of a person's in a real time video image is encoded into a compact sequence of multi scale quadrature 2D Gabor wavelet coefficients, whose most significant bits comprise a 256 byte iris code. Statistical decision theory generates identification decisions from Exclusive OR comparisons of complete codes at the rate of 10,000 per second, including calculation of decision confidence levels. The distributions observed empirically in such comparisons imply a theoretical cross over error rate of one in 131,000 when a decision criterion is adopted that would equalise the false accept and false reject error rates. In the typical recognition case, given the mean observed degree of code agreement, the decision confidence levels correspond formally to a conditional false accept probability of one in about 10/sup 31/.