  A novel minutia-based fingerprint matching algorithm is proposed that employs
iterative global alignment on two minutia sets. The matcher considers all
possible minutia pairings and iteratively aligns the two sets until the number
of minutia pairs does not exceed the maximum number of allowable one-to-one
pairings. The optimal alignment parameters are derived analytically via linear
least squares. The first alignment establishes a region of overlap between the
two minutia sets, which is then (iteratively) refined by each successive
alignment. After each alignment, minutia pairs that exhibit weak correspondence
are discarded. The process is repeated until the number of remaining pairs no
longer exceeds the maximum number of allowable one-to-one pairings. The
proposed algorithm is tested on both the FVC2000 and FVC2002 databases, and the
results indicate that the proposed matcher is both effective and efficient for
fingerprint authentication; it is fast and does not utilize any computationally
expensive mathematical functions (e.g. trigonometric, exponential). In addition
to the proposed matcher, another contribution of the paper is the analytical
derivation of the least squares solution for the optimal alignment parameters
for two point-sets lacking exact correspondence.
