%0 Conference Proceedings
%T New Algorithmic Approaches to Point Constellation Recognition
%+ Construction and Analysis of Systems for Confidentiality and Authenticity of Data and Entities (CASCADE)
%+ Morpho
%+ CROCUS Technology
%A Bourgeat, Thomas
%A Bringer, Julien
%A Chabanne, Hervé
%A Champenois, Robin
%A Clément, Jérémie
%A Ferradi, Houda
%A Heinrich, Marc
%A Melotti, Paul
%A Naccache, David
%A Voizard, Antoine
%Z Part 2: Data Security
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 29th IFIP International Information Security Conference (SEC)
%C Marrakech, Morocco
%Y Nora Cuppens-Boulahia
%Y Frédéric Cuppens
%Y Sushil Jajodia
%Y Anas Abou El Kalam
%Y Thierry Sans
%I Springer
%3 ICT Systems Security and Privacy Protection
%V AICT-428
%P 80-90
%8 2014-06-02
%D 2014
%R 10.1007/978-3-642-55415-5_7
%Z Computer Science [cs]Conference papers
%X 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.
%G English
%Z TC 11
%2 https://inria.hal.science/hal-01098401v2/document
%2 https://inria.hal.science/hal-01098401v2/file/978-3-642-55415-5_7_Chapter.pdf
%L hal-01098401
%U https://inria.hal.science/hal-01098401
%~ ENS-PARIS
%~ CNRS
%~ INRIA
%~ INRIA-ROCQ
%~ TESTALAIN1
%~ IFIP
%~ IFIP-AICT
%~ INRIA2
%~ IFIP-TC
%~ IFIP-AICT-428
%~ IFIP-TC11
%~ IFIP-SEC
%~ PSL
%~ INRIA-PSL
%~ ENS-PSL
%~ DIENS