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Biomet: A multimodal person authentication database including face, voice, fingerprint, hand and signature modalities

  • Sonia Garcia-Salicetti
  • , Charles Beumier
  • , Gérard Chollet
  • , Bernadette Dorizzi
  • , Jean Leroux Les Jardins
  • , Jan Lunter
  • , Yang Ni
  • , Dijana Petrovska-Delacrétaz
  • CNRS SAMOVAR UMR 5157
  • Koninklijke Militaire School - Ecole Royale Militaire
  • Telecom Paris
  • University of Fribourg

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Information technology innovations involve a constant evolution of man-machine interaction modes. Automated authentication of people could be used to better adapt the machine to the user. Security can also be enhanced through a better people authentication. Biometrics appears as a promising tool in these two situations. Different modalities can be envisaged, such as: fingerprint, human face images, hand shape, voice, handwritten signature... In order to take advantage of the particularities of each modality, and to improve the performance of a person authentication system, multimodality can be applied. This motivated the recording of BIOMET, a biometric database with five different modalities, including face, voice, fingerprint, hand and signature data. In this paper, the BIOMET multimodal database for person authentication is described. Details about the acquisition protocols of each modality are given. Preliminary monomodal verification results, obtained on a subcorpus of the BIOMET fingerprint data, are also presented.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsJosef Kittler, Mark S. Nixon
PublisherSpringer Verlag
Pages845-853
Number of pages9
ISBN (Electronic)9783540403029
DOIs
Publication statusPublished - 1 Jan 2003
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2688
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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