New Algorithmic Approaches to Point Constellation Recogniti

Thomas Bourgeat 1 Julien Bringer 2 Hervé Chabanne 3 Robin Champenois 1 Jérémie Clément 1 Houda Ferradi 4, 1 Marc Heinrich 1 Paul Melotti 1 David Naccache 1, 4 Antoine Voizard 1
1 CASCADE - Construction and Analysis of Systems for Confidentiality and Authenticity of Data and Entities
DI-ENS - Département d'informatique de l'École normale supérieure, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR 8548
3 CIRTAI-IDEES - Centre interdisciplinaire de recherche en transports et affaires internationales
IDEES - Identités et Différenciation de l'Environnement des Espaces et des Sociétés
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.
Keywords : fingerprits Biometry
Type de document :
Rapport
[Technical Report] CoRR abs/1405.1402 (2014), Ecole normale supérieure. 2014, pp.14
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https://hal.inria.fr/hal-01098399
Contributeur : David Naccache <>
Soumis le : mercredi 24 décembre 2014 - 14:33:52
Dernière modification le : jeudi 11 janvier 2018 - 06:22:10

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Thomas Bourgeat, Julien Bringer, Hervé Chabanne, Robin Champenois, Jérémie Clément, et al.. New Algorithmic Approaches to Point Constellation Recogniti. [Technical Report] CoRR abs/1405.1402 (2014), Ecole normale supérieure. 2014, pp.14. 〈hal-01098399〉

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