# A New Point-set Registration Algorithm for Fingerprint Matching

## TL;DR

This paper introduces a fast, iterative minutia-based fingerprint matching algorithm that optimally aligns two point-sets without exact correspondence, demonstrating effectiveness and efficiency on standard databases.

## Contribution

It presents a novel iterative global alignment method for fingerprint minutiae that analytically derives optimal parameters without computationally expensive functions.

## Key findings

- Effective on FVC2000 and FVC2002 databases
- Fast and computationally efficient
- No use of trigonometric or exponential functions

## Abstract

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.