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Iris code

Iris code

Each isolated iris pattern is then demodulated to extract its phase information using quadrature 2-D Gaborwavelets. It amounts to a patch-wise phase quantization of the iris pattern, by identifying in which quadrant of the complex plane each resultant phasor lies when a given area of the iris is projected onto complex- valued 2-D Gabor wavelets. Only phase information is used for recognizing irises because amplitude information is not very discriminating, and it depends upon extraneous factors such as imaging contrast, illumination, and camera gain. The phase bit settings which code the sequence of projection quadrants capture the information of wavelet zero-crossings, as is clear from the sign operator in. The extraction of phase has the further advantage that phase angles remain defined regardless of how poor the image contrast may be. Its phase bit stream has statistical properties such as run lengths similar to those of the code for the properly focused eye image. The benefit which arises from the fact that phase bits are set also for a poorly focused image as shown here, even if based only on random CCD thermal noise, is that different poorly focused irises never become confused with each other when their phase codes are compared. By contrast, images of different faces look increasingly alike when poorly resolved and can be confused with each other by appearance-based face recognition algorithms. this test is virtually guaranteed to be passed whenever the phase codes for two different eyes are compared, but to be uniquely failed when any eye’s phase code is compared with another version of itself.

The test of statistical independence is implemented by the simple Boolean Exclusive-OR operator (XOR) applied to the 2048 bit phase vectors that encode any two iris patterns, masked (AND’ed) by both of their corresponding mask bit vectors to prevent noniris artifacts from influencing iris comparisons. The XOR operator detects disagreement between any corresponding pair of bits, while the AND operator ensures that the compared bits are both deemed to have been uncorrupted by eyelashes, eyelids, specular reflections, or other noise. The norms (|| ||) of the resultant bit vector and of the AND’ed mask vectors are then measured in order to compute a fractional Hamming Distance (HD) as the measure of the dissimilarity between any two irises, whose two phase code bit vectors are denoted {codeA, codeB} and whose mask bit vectors are denoted {maskA, maskB}:

The denominator tallies the total number of phase bits that mattered in iris comparisons after artifacts such as eyelashes and specular reflections were discounted, so the resulting HD is a fractional measure of dissimilarity; 0 would represent a perfect match. The Boolean operators and are applied in vector form to binary strings of length up to the word length of the CPU, as a single machine instruction. Thus, for example on an ordinary 32-b machine, any two integers between 0 and 4 billion can be XOR’ed in a single machine instruction to generate a third such integer, each of whose bits in a binary expansion is the XOR of the corresponding pair of bits of the original two integers. This implementation of in parallel 32-b chunks enables extremely rapid comparisons of iris codes when searching through a large database to find a match. On a 300-MHz CPU, such exhaustive searches are performed at a rate of about 100 000 irises per second.

HD	Odds of false match
0.26	1:1013
0.27	1:1012
0.28	1:1011
0.29	1:13 000 000 000
0.30	1:1.5 000 000
0.31	1:185 000 000
0.32	1:26 000 000
0.33	1:4 000 000
0.34	1:690,000
0.35	1:133,000

Table: CUMULATIVES UNDER GIVING SINGLE FALSE MATCH PROBABILITIES FOR VARIOUS HD CRITERIA

How Iris Recognition Works - John Daugman, PhD, OBE, University of Cambridge