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We propose a variant of Ising model, called the Seeded Ising Model, to modelprobabilistic nature of human iris templates. This model is an Ising model inwhich the values at certain lattice points are held fixed throughout Isingmodel evolution. Using this we show how to reconstruct the full iris templatefrom partial information, and we show that about 1/6 of the given template isneeded to recover almost all information content of the original one in thesense that the resulting Hamming distance is well within the range to assertcorrectly the identity of the subject. This leads us to propose the concept ofeffective statistical degree of freedom of iris templates and show it is about1/6 of the total number of bits. In particular, for a template of $2048$ bits,its effective statistical degree of freedom is about $342$ bits, whichcoincides very well with the degree of freedom computed by the completelydifferent method proposed by Daugman.

Seeded Ising Model and Statistical Natures of Human Iris Templates