Title :
High confidence visual recognition of persons by a test of statistical independence
Author :
Daugman, John G.
Author_Institution :
Fac. of Biol., Cambridge Univ., UK
fDate :
11/1/1993 12:00:00 AM
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. The visible texture of a person´s iris in a real-time video image is encoded into a compact sequence of multi-scale quadrature 2-D 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 iris codes at the rate of 4000 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 131000 when a decision criterion is adopted that would equalize the false accept and false reject error rates. In the typical recognition case, given the mean observed degree of iris code agreement, the decision confidence levels correspond formally to a conditional false accept probability of one in about 1031
Keywords :
decision theory; face recognition; feature extraction; image coding; image texture; statistical analysis; decision confidence levels; exclusive-OR; face recognition; false accept error rates; false reject error rates; iris code; multiscale quadrature 2-D Gabor wavelet coefficients; personal identity recognition; phenotypic feature; probability; rapid visual recognition; statistical decision theory; statistical independence test; Biometrics; Decision theory; Error analysis; Face; Fingerprint recognition; Humans; Image texture analysis; Iris; Pattern recognition; Testing;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on