The Experts below are selected from a list of 155610 Experts worldwide ranked by ideXlab platform
Paul Melotti - One of the best experts on this subject based on the ideXlab platform.
-
new algorithmic approaches to point Constellation recognition
Information Security Conference, 2014Co-Authors: Thomas Bourgeat, Julien Bringer, Herve Chabanne, Robin Champenois, Jeremie Clement, Houda Ferradi, Marc Heinrich, Paul MelottiAbstract: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.
-
new algorithmic approaches to point Constellation recognition
arXiv: Computer Vision and Pattern Recognition, 2014Co-Authors: Thomas Bourgeat, Julien Bringer, Herve Chabanne, Robin Champenois, Jeremie Clement, Houda Ferradi, Marc Heinrich, Paul MelottiAbstract: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.
Jeremie Clement - One of the best experts on this subject based on the ideXlab platform.
-
new algorithmic approaches to point Constellation recognition
Information Security Conference, 2014Co-Authors: Thomas Bourgeat, Julien Bringer, Herve Chabanne, Robin Champenois, Jeremie Clement, Houda Ferradi, Marc Heinrich, Paul MelottiAbstract: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.
-
new algorithmic approaches to point Constellation recognition
arXiv: Computer Vision and Pattern Recognition, 2014Co-Authors: Thomas Bourgeat, Julien Bringer, Herve Chabanne, Robin Champenois, Jeremie Clement, Houda Ferradi, Marc Heinrich, Paul MelottiAbstract: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.
Houda Ferradi - One of the best experts on this subject based on the ideXlab platform.
-
new algorithmic approaches to point Constellation recognition
Information Security Conference, 2014Co-Authors: Thomas Bourgeat, Julien Bringer, Herve Chabanne, Robin Champenois, Jeremie Clement, Houda Ferradi, Marc Heinrich, Paul MelottiAbstract: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.
-
new algorithmic approaches to point Constellation recognition
arXiv: Computer Vision and Pattern Recognition, 2014Co-Authors: Thomas Bourgeat, Julien Bringer, Herve Chabanne, Robin Champenois, Jeremie Clement, Houda Ferradi, Marc Heinrich, Paul MelottiAbstract: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.
Rui Dinis - One of the best experts on this subject based on the ideXlab platform.
-
Designing Good Multi-Dimensional Constellations
IEEE Wireless Communications Letters, 2012Co-Authors: Marko Beko, Rui DinisAbstract:In this letter we consider the design of multi-dimensional compact Constellations that minimize the average symbol energy for a given minimum Euclidian distance between Constellation points. We formulate the Constellation design as a non-convex quadratically constrained quadratic programming. We propose a simple and efficient optimization method, which offers good solutions for small to medium sized Constellations.
Jyh-ching Juang - One of the best experts on this subject based on the ideXlab platform.
-
On Solving the Multi-Constellation Pseudorange Equations
Annual of Navigation, 2010Co-Authors: Jyh-ching JuangAbstract:Future Global Navigation Satellite System (GNSS) receivers may employ a combination of different navigation satellite Constellations to provide positioning, navigation, and timing information. As different Constellations may not be time-synchronized, the multi-Constellation navigation problem involves the determination of position of the receiver and clock bias with respect to each Constellation. Even though iterative and linearization method may remain applicable for terrestrial users when the initial position error is not too significant, the fact that the multi-Constellation navigation equations are augmented with additional unknowns demands some investigation into the resulting solvability. In this paper, a spectral decomposition approach is proposed to characterize all admissible solutions of a multi-Constellation navigation problem. The solvability of the problem is addressed, all potential solutions are determined, and the navigation errors are analyzed. By applying the proposed algorithm to envisioned future multi-Constellation navigation problems, some potential pitfalls in combined GPS+QZSS and GPS+Galileo navigation are identified.
-
On exact solutions of the multi-Constellation GNSS navigation problem
GPS Solutions, 2009Co-Authors: Jyh-ching Juang, Yung Fu TsaiAbstract:In Global Navigation Satellite System (GNSS) positioning, the receiver measures the pseudorange with respect to each observable navigation satellite and determines the position and clock bias. In addition to the GPS, several other navigation satellite Constellations including Glonass, Galileo and Compass can/will also be used to provide positioning, navigation, and timing information. The paper is concerned with the solvability of the navigation problem when the receiver attempts to process measurements from different Constellations. As two different Constellations may not be time-synchronized, the navigation problem involves the determination of position of the receiver and clock bias with respect to each Constellation. The paper describes an analytic approach to account for the two-Constellation navigation problem with three measurements from one Constellation and two measurements from another Constellation. It is shown that the two-Constellation GNSS navigation problem becomes the solving of a set of two simultaneous quadratic equations or, equivalently, a quartic equation. Furthermore, the zero-crossover of the leading coefficient and the sign of the discriminant of the quartic equation are shown to play a significant role in governing the solvability, i.e., the existence and uniqueness of the navigation solutions.
