A hyperbolic function model for multiple biometrics decision fusion

Kar Ann Toh, Xudong Jiang, Wei Yun Yau

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this paper, we treat the problem of combining fingerprint and speech biometric decisions as a classifier fusion problem. The Feed-forward Neural Network provides a natural choice for such data fusion as it has been shown to be a universal approximator. However, the training process remains much to be a trial-and-error effort since no learning algorithm can guarantee convergence to optimal solution within finite iterations. In this work, we propose a network model to generate different combinations of the hyperbolic functions to achieve some approximation and classification properties. This is to circumvent the iterative training problem as seen in neural networks learning. The proposed hyperbolic functions network model is applied to combine the fingerprint and speaker verification decisions which show either better or comparable results with respect to several commonly used methods.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsDavid Zhang, Anil K. Jain
PublisherSpringer Verlag
Pages655-662
Number of pages8
ISBN (Print)3540221468, 9783540221463
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3072
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Toh, K. A., Jiang, X., & Yau, W. Y. (2004). A hyperbolic function model for multiple biometrics decision fusion. In D. Zhang, & A. K. Jain (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 655-662). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3072). Springer Verlag. https://doi.org/10.1007/978-3-540-25948-0_89