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    Authentication of individuals using hand geometry biometrics: a neural network approach.

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    Date
    2007-12-01
    Author
    Elizondo, David;
    Faundez-Zanuy, Marcus;
    Ferrer-Ballester, M. A.;
    Travieso-Gonzalez, C. M.
    Metadata
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    Description
    This paper introduces an inexpensive, powerful and easy to use hand geometry based biometric person authentication system using neural networks. The proposed approach followed to construct this system consists of an acquisition device, a pre-processing stage, and a neural network based classifier. One of the novelties of this work is the introduction of hand geometry-related, position independent, feature extraction and identification which can be useful in problems related to image processing and pattern recognition. Another novelty of this research is the use of error correction codes to enhance the level of performance of the neural network model.
    Citation : Faundez-Zanuy, M. et al. (2007) Authentication of individuals using hand geometry biometrics: a neural network approach. Neural Processing Letters, 26(3), pp. 201-216.
    URI
    http://hdl.handle.net/2086/174
    DOI
    http://dx.doi.org/10.1007/s11063-007-9052-y
    ISSN : 1573-773X
    Research Group : DIGITS
    Research Group : Centre for Computational Intelligence
    Research Institute : Institute of Artificial Intelligence (IAI)
    Peer Reviewed : Yes
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    • School of Computer Science and Informatics [2973]

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