Fundamental Study of Neonate Fingerprint Recognition Using Fingerprint Classification

被引:0
|
作者
Koda, Yoshinori [1 ]
Imai, Haruki [1 ]
Sasuga, Nagisa [2 ]
Ito, Koichi [2 ]
Aoki, Takafumi [2 ]
Kaneko, Satoshi [3 ]
Nzou, Samson Muuo [4 ]
机构
[1] NEC Corp Ltd, Biometr Res Labs, Kawasaki, Japan
[2] Tohoku Univ, Grad Sch Informat Sci, Sendai, Japan
[3] Nagasaki Univ, Inst Trop Med, Nagasaki, Japan
[4] Kenya Govt Med Res Ctr, Ctr Microbiol Res, Nairobi, Kenya
来源
PROCEEDINGS OF THE 21ST 2022 INTERNATIONAL CONFERENCE OF THE BIOMETRICS SPECIAL INTEREST GROUP (BIOSIG 2022) | 2022年 / P-329卷
关键词
Fingerprint recognition; Neonate fingerprint; Fingerprint scanner; Pattern classification;
D O I
10.1109/BIOSIG55365.2022.9897017
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Fundamental research on the fingerprint recognition algorithm
    Li, Binyao
    Dai, Fengzhi
    Wang, Dejin
    Zhang, Baolong
    Kushida, Naoki
    PROCEEDINGS OF THE SEVENTEENTH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL LIFE AND ROBOTICS (AROB 17TH '12), 2012, : 394 - 397
  • [2] Longitudinal study of fingerprint recognition
    Yoon, Soweon
    Jain, Anil K.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2015, 112 (28) : 8555 - 8560
  • [3] Fingerprint classification system using CNN
    Nahar, Prateek
    Chaudhari, N. S.
    Tanwani, S. K.
    MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (17) : 24515 - 24527
  • [4] Empirical study on touchless fingerprint recognition using a phone camera
    Noh, Donghyun
    Lee, Wonjune
    Son, Byungjun
    Kim, Jaihie
    JOURNAL OF ELECTRONIC IMAGING, 2018, 27 (03)
  • [5] Research of Fingerprint Recognition
    Jiang, Chunfeng
    Zhao, Yulan
    Xu, Wei
    Meng, Xiangping
    EIGHTH IEEE INTERNATIONAL CONFERENCE ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, PROCEEDINGS, 2009, : 847 - +
  • [6] AUTOMATED FINGERPRINT RECOGNITION USING STRUCTURAL MATCHING
    HRECHAK, AK
    MCHUGH, JA
    PATTERN RECOGNITION, 1990, 23 (08) : 893 - 904
  • [7] Fingerprint Recognition Using Artificial Neural Networks
    Singh, Raghvendra
    Singh, Rajendra
    Tripathi, Rajendra Kumar
    Agarwal, Prateek
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES INDIA SECTION A-PHYSICAL SCIENCES, 2025, : 127 - 135
  • [8] Evaluation of Supervised Machine Learning Classification Algorithms for Fingerprint Recognition
    Rojas, Andres
    Dolecek, Gordana Jovanovic
    PROCEEDINGS OF 2021 GLOBAL CONGRESS ON ELECTRICAL ENGINEERING (GC-ELECENG 2021), 2021, : 1 - 4
  • [9] Impact of digital fingerprint image quality on the fingerprint recognition accuracy
    Mohammad A. Alsmirat
    Fatimah Al-Alem
    Mahmoud Al-Ayyoub
    Yaser Jararweh
    Brij Gupta
    Multimedia Tools and Applications, 2019, 78 : 3649 - 3688
  • [10] Impact of digital fingerprint image quality on the fingerprint recognition accuracy
    Alsmirat, Mohammad A.
    Al-Alem, Fatimah
    Al-Ayyoub, Mahmoud
    Jararweh, Yaser
    Gupta, Brij
    MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (03) : 3649 - 3688