Fundamental Study of Neonate Fingerprint Recognition Using Fingerprint Classification

Yoshinori Koda, Haruki Imai, Nagisa Sasuga, Koichi Ito, Takafumi Aoki, Satoshi Kaneko, Samson Muuo Nzou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

UNICEF reported that many of the 2.4 million deaths within 28 days of birth were preventable with appropriate vaccination. There are several reasons why babies cannot be vaccinated, for example, the medical staff does not have appropriate vaccination history management to control who and when they should be vaccinated. To properly manage vaccination history and promote its widespread use, personal identification after birth is essential, and a neonate fingerprint identification technology could be one of the solutions. In this paper, we develop a fingerprint scanner with a 2,674ppi high-resolution CMOS sensor specifically designed to acquire neonatal fingerprints by integrating positive comments from users in the research field on the previous prototype. We also propose a neonate fingerprint identification method based on fingerprint classification.

Original languageEnglish
Title of host publicationBIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group
EditorsArslan Bromme, Naser Damer, Marta Gomez-Barrero, Kiran Raja, Christian Rathgeb, Ana F. Sequeira, Massimiliano Todisco, Andreas Uhl
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9783885797234
DOIs
Publication statusPublished - 2022
Event21st International Conference of the Biometrics Special Interest Group, BIOSIG 2022 - Darmstadt, Germany
Duration: 2022 Sept 142022 Sept 16

Publication series

NameBIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group

Conference

Conference21st International Conference of the Biometrics Special Interest Group, BIOSIG 2022
Country/TerritoryGermany
CityDarmstadt
Period22/9/1422/9/16

Keywords

  • Fingerprint recognition
  • Fingerprint scanner
  • Neonate fingerprint
  • Pattern classification

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