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

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dc.contributor.author Elizondo, David en
dc.contributor.author Faundez-Zanuy, Marcus en
dc.contributor.author Ferrer-Ballester, M. A. en
dc.contributor.author Travieso-Gonzalez, C. M. en
dc.date.accessioned 2008-11-24T13:24:11Z
dc.date.available 2008-11-24T13:24:11Z
dc.date.issued 2007-12-01 en
dc.identifier.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.
dc.identifier.issn 1573-773X en
dc.identifier.uri http://hdl.handle.net/2086/174
dc.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. en
dc.language.iso en en
dc.publisher Springer Verlag en
dc.subject RAE 2008
dc.subject UoA 23 Computer Science and Informatics
dc.subject biometrics
dc.subject hand geometry
dc.subject neural network
dc.subject biometrical features
dc.subject feature extraction
dc.subject feature identification
dc.subject authentication of individual
dc.title Authentication of individuals using hand geometry biometrics: a neural network approach. en
dc.type Article en
dc.identifier.doi http://dx.doi.org/10.1007/s11063-007-9052-y en
dc.researchgroup DIGITS en
dc.researchgroup Centre for Computational Intelligence
dc.peerreviewed Yes


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