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New Algorithmic Approaches to Point Constellation Recognition

Thomas Bourgeat 1 Julien Bringer 2 Hervé Chabanne 2 Robin Champenois 1 Jérémie Clément 1, 3 Houda Ferradi 1, 2 Marc Heinrich 1 Paul Melotti 1 David Naccache 1 Antoine Voizard 1
1 CASCADE - Construction and Analysis of Systems for Confidentiality and Authenticity of Data and Entities
Inria de Paris, CNRS - Centre National de la Recherche Scientifique : UMR 8548, DI-ENS - Département d'informatique de l'École normale supérieure
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.
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Thomas Bourgeat, Julien Bringer, Hervé Chabanne, Robin Champenois, Jérémie Clément, et al.. New Algorithmic Approaches to Point Constellation Recognition. 29th IFIP International Information Security Conference (SEC), Jun 2014, Marrakech, Morocco. pp.80-90, ⟨10.1007/978-3-642-55415-5_7⟩. ⟨hal-01098401v2⟩

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