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Spiral Topologies for Biometric Recognition

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Advanced Studies in Biometrics

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3161))

Abstract

Biometric recognition has attracted the attention of scientists, investors, government agencies as well as the media for the great potential in many application domains. It turns out that there are still a number of intrinsic drawbacks in all biometric techniques. In this paper we postulate the need for a proper data representation which may simplify and augment the discrimination among different instances or biometric samples of different subjects. Considering the design of many natural systems it turns out that spiral (circular) topologies are the best suited to economically store and process data. Among the many developed techniques for biometric recognition, face analysis seems to be the most promising and interesting modality. The ability of the human visual system of analyzing unknown faces, is an example of the amount of information which can be extracted from face images. Nonetheless, there are still many open problems which need to be ”faced” as well. The choice of optimal resolution of the face within the image, face registration and facial feature extraction are still open issues. This not only requires to devise new algorithms but to determine the real potential and limitations of existing techniques. In this paper two different methods for face matching are presented, based on the same similarity measure but on different image representations. The methods are tested with conventional and also new databases, obtained from real subjects in real working environments.

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Author information

Authors and Affiliations

  1. Computer Vision Laboratory, University of Sassari, piazza Duomo, 6, 07041, Alghero (SS), Italy

    Massimo Tistarelli & Enrico Grosso

  2. Computer Vision Laboratory, DIST – University of Genova, via Opera Pia, 13, 16145, Genova, Italy

    Andrea Lagorio

Authors
  1. Massimo Tistarelli
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  2. Enrico Grosso
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  3. Andrea Lagorio
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Editors and Affiliations

  1. University of Sassari, 07041, Alghero, Italy

    Massimo Tistarelli

  2. School of Information Science, Computer and Electrical Engineering (IDE), Halmstad University, Box 823, SE-301 18, Halmstad

    Josef Bigun

  3. DEIR - University of Sassari, Sassari, Italy

    Enrico Grosso

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Tistarelli, M., Grosso, E., Lagorio, A. (2005). Spiral Topologies for Biometric Recognition. In: Tistarelli, M., Bigun, J., Grosso, E. (eds) Advanced Studies in Biometrics. Lecture Notes in Computer Science, vol 3161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11493648_4

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  • DOI: https://doi.org/10.1007/11493648_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26204-6

  • Online ISBN: 978-3-540-28638-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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