New Algorithmic Approaches to Point Constellation Recognition
This work addresses fingerprint verification challenges, but appears incremental as it builds on prior methods.
The paper tackles the problem of point constellation recognition, particularly for fingerprint matching, by presenting three new algorithms, including one that draws an analogy to mechanical system simulation.
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.