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Registration of Fingerprints by Complex Filtering and by 1D Projections of Orientation Images

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Audio- and Video-Based Biometric Person Authentication (AVBPA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3546))

Abstract

When selecting a registration method for fingerprints, the choice is often between a minutiae based or an orientation field based registration method. In selecting a combination of both methods, instead of selecting one of the methods, we obtain a one modality multi-expert registration system. If the combined methods are based on different features in the fingerprint, e.g. the minutiae points respective the orientation field, they are uncorrelated and a higher registration performance can be expected compared to when only one of the methods are used. In this paper two registration methods are discussed that do not use minutiae points, and are therefore candidates to be combined with a minutiae based registration method to build a multi-expert registration system for fingerprints with expected high registration performance. Both methods use complex orientations fields but produce uncorrelated results by construction. One method uses the position and geometric orientation of symmetry points, i.e. the singular points (SPs) in the fingerprint to estimate the translation respectively the rotation parameter in the Euclidean transformation. The second method uses 1D projections of orientation images to find the transformation parameters. Experimental results are reported.

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© 2005 Springer-Verlag Berlin Heidelberg

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Nilsson, K., Bigun, J. (2005). Registration of Fingerprints by Complex Filtering and by 1D Projections of Orientation Images. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_18

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  • DOI: https://doi.org/10.1007/11527923_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27887-0

  • Online ISBN: 978-3-540-31638-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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