New Algorithmic Approaches to Point Constellation Recognition
Abstract
Point constellation recognition is a common problem with many pattern matching applications. Whilst useful in many contexts, this work is mainly motivated by fingerprint matching. Fingerprints are traditionally modelled as constellations of oriented points called minutiae. The fingerprint verifier's task consists in comparing two point constellations. The compared constellations may differ by rotation and translation or by much more involved transforms such as distortion or occlusion. This paper presents three new constellation matching algorithms. The first two methods generalize an algorithm by Bringer and Despiegel. Our third proposal creates a very interesting analogy between mechanical system simulation and the constellation recognition problem.
Cite
@article{arxiv.1405.1402,
title = {New Algorithmic Approaches to Point Constellation Recognition},
author = {Thomas Bourgeat and Julien Bringer and Herve Chabanne and Robin Champenois and Jeremie Clement and Houda Ferradi and Marc Heinrich and Paul Melotti and David Naccache and Antoine Voizard},
journal= {arXiv preprint arXiv:1405.1402},
year = {2014}
}
Comments
14 pages, short version submitted to SEC 2014