The first stage of iris recognition is to locate an iris within an image. An Integro-differential operator is used for this, which finds all circles in an image. The sum of pixel values within each circle is calculated, and then the values of adjacent circles are compared. The iris is detected as the circle with the maximum difference from its adjacent circles.

The next stage is to unwrap the detected iris, which transforms the circular iris into a rectangular image. An iris code is then generated from the unwrapped iris, which can be used for comparisons.

Comparisons are done using the Hamming distance function, which compares each bit of the iris code and counts the proportion of non-matching bits, which is then normalised by the total number of valid bits. If the hamming distance between two iris codes is found to be below a given threshold then those two iris are likely to be the same.

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