TY - GEN
T1 - Fundamental Study of Neonate Fingerprint Recognition Using Fingerprint Classification
AU - Koda, Yoshinori
AU - Imai, Haruki
AU - Sasuga, Nagisa
AU - Ito, Koichi
AU - Aoki, Takafumi
AU - Kaneko, Satoshi
AU - Nzou, Samson Muuo
N1 - Funding Information:
Authors hereby declare that the parents or guardians of babies who join this research were properly requested to sign onto a consent form as a permission of their participation for this research. This research is appropriately approved by Scientific Ethics Review Unit (SERU) of Kenya Medical Research Institute (KEMRI) before data collection. The author(s) disclose the receipt of the extraordinary on-site assistance for the research of this article from supporters in Kenya and we hereby express our gratitude for Kwale county government, Kenya, NUITM-KEMRI project office in Kenya of Nagasaki University Institute of Tropical Medicine, and The Center for Microbiology Research, KEMRI, and the Director General, KEMRI.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Fingerprint recognition
KW - Fingerprint scanner
KW - Neonate fingerprint
KW - Pattern classification
UR - http://www.scopus.com/inward/record.url?scp=85141083878&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85141083878&partnerID=8YFLogxK
U2 - 10.1109/BIOSIG55365.2022.9897017
DO - 10.1109/BIOSIG55365.2022.9897017
M3 - Conference contribution
AN - SCOPUS:85141083878
T3 - BIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group
BT - BIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group
A2 - Bromme, Arslan
A2 - Damer, Naser
A2 - Gomez-Barrero, Marta
A2 - Raja, Kiran
A2 - Rathgeb, Christian
A2 - Sequeira, Ana F.
A2 - Todisco, Massimiliano
A2 - Uhl, Andreas
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st International Conference of the Biometrics Special Interest Group, BIOSIG 2022
Y2 - 14 September 2022 through 16 September 2022
ER -
