  We propose a variant of Ising model, called the Seeded Ising Model, to model
probabilistic nature of human iris templates. This model is an Ising model in
which the values at certain lattice points are held fixed throughout Ising
model evolution. Using this we show how to reconstruct the full iris template
from partial information, and we show that about 1/6 of the given template is
needed to recover almost all information content of the original one in the
sense that the resulting Hamming distance is well within the range to assert
correctly the identity of the subject. This leads us to propose the concept of
effective statistical degree of freedom of iris templates and show it is about
1/6 of the total number of bits. In particular, for a template of $2048$ bits,
its effective statistical degree of freedom is about $342$ bits, which
coincides very well with the degree of freedom computed by the completely
different method proposed by Daugman.
