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  • 1.
    Bigun, Josef
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Tomas
    TietoEnator AB, Storg. 3, 58223 Linköping, Sweden.
    Nilsson, Kenneth
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Recognition by symmetry derivatives and the generalized structure tensor2004Inngår i: IEEE Transaction on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, E-ISSN 1939-3539, Vol. 26, nr 12, s. 1590-1605Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We suggest a set of complex differential operators that can be used to produce and filter dense orientation (tensor) fields for feature extraction, matching, and pattern recognition. We present results on the invariance properties of these operators, that we call symmetry derivatives. These show that, in contrast to ordinary derivatives, all orders of symmetry derivatives of Gaussians yield a remarkable invariance: they are obtained by replacing the original differential polynomial with the same polynomial, but using ordinary coordinates x and y corresponding to partial derivatives. Moreover, the symmetry derivatives of Gaussians are closed under the convolution operator and they are invariant to the Fourier transform. The equivalent of the structure tensor, representing and extracting orientations of curve patterns, had previously been shown to hold in harmonic coordinates in a nearly identical manner. As a result, positions, orientations, and certainties of intricate patterns, e.g., spirals, crosses, parabolic shapes, can be modeled by use of symmetry derivatives of Gaussians with greater analytical precision as well as computational efficiency. Since Gaussians and their derivatives are utilized extensively in image processing, the revealed properties have practical consequences for local orientation based feature extraction. The usefulness of these results is demonstrated by two applications:

    1. tracking cross markers in long image sequences from vehicle crash tests and
    2. alignment of noisy fingerprints.
  • 2.
    Ortega-Garcia, Javier
    et al.
    Universidad Autonoma de Madrid, Madrid, Spain.
    Fierrez, Julian
    Universidad Autonoma de Madrid, Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Galbally, Javier
    Universidad Autonoma de Madrid, Madrid, Spain.
    Freire, Manuel R.
    Universidad Autonoma de Madrid, Madrid, Spain.
    Gonzalez-Rodriguez, Joaquin
    Universidad Autonoma de Madrid, Madrid, Spain.
    Garcia-Mateo, Carmen
    Universidad Autonoma de Madrid, Madrid, Spain.
    Alba-Castro, Jose-Luis
    Universidad Autonoma de Madrid, Madrid, Spain.
    Gonzalez-Agulla, Elisardo
    Universidad Autonoma de Madrid, Madrid, Spain.
    Otero-Muras, Enrique
    Universidad Autonoma de Madrid, Madrid, Spain.
    Garcia-Salicetti, Sonia
    Universidad Autonoma de Madrid, Madrid, Spain.
    Allano, Lorene
    Universidad Autonoma de Madrid, Madrid, Spain.
    Ly-Van, Bao
    Universidad Autonoma de Madrid, Madrid, Spain.
    Dorizzi, Bernadette
    Universidad Autonoma de Madrid, Madrid, Spain.
    Kittler, Josef
    Universidad Autonoma de Madrid, Madrid, Spain.
    Bourlai, Thirimachos
    Universidad Autonoma de Madrid, Madrid, Spain.
    Poh, Norman
    Universidad Autonoma de Madrid, Madrid, Spain.
    Deravi, Farzin
    Universidad Autonoma de Madrid, Madrid, Spain.
    Ng, Ming W. R.
    Universidad Autonoma de Madrid, Madrid, Spain.
    Fairhurst, Michael
    Universidad Autonoma de Madrid, Madrid, Spain.
    Hennebert, Jean
    Universidad Autonoma de Madrid, Madrid, Spain.
    Humm, Andreas
    Universidad Autonoma de Madrid, Madrid, Spain.
    Tistarelli, Massimo
    Universidad Autonoma de Madrid, Madrid, Spain.
    Brodo, Linda
    Universidad Autonoma de Madrid, Madrid, Spain.
    Richiardi, Jonas
    Universidad Autonoma de Madrid, Madrid, Spain.
    Drygajlo, Andrzej
    Universidad Autonoma de Madrid, Madrid, Spain.
    Ganster, Harald
    Universidad Autonoma de Madrid, Madrid, Spain.
    Sukno, Federico M.
    Universidad Autonoma de Madrid, Madrid, Spain.
    Pavani, Sri-Kaushik
    Universidad Autonoma de Madrid, Madrid, Spain.
    Frangi, Alejandro
    Universidad Autonoma de Madrid, Madrid, Spain.
    Akarun, Lale
    Universidad Autonoma de Madrid, Madrid, Spain.
    Savran, Arman
    Universidad Autonoma de Madrid, Madrid, Spain.
    The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)2010Inngår i: IEEE Transaction on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, E-ISSN 1939-3539, Vol. 32, nr 6, s. 1097-1111Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008. © 2010 IEEE.

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