Infant-ID: Fingerprints for Global Good
Not on the map. Why?
Abstract (arXiv)
In many of the least developed and developing countries, a multitude of infants continue to suffer and die from vaccine-preventable diseases and malnutrition. Lamentably, the lack of official identification documentation makes it exceedingly difficult to track which infants have been vaccinated and which infants have received nutritional supplements. Answering these questions could prevent this infant suffering and premature death around the world. To that end, we propose Infant-Prints, an end-to-end, low-cost, infant fingerprint recognition system. Infant-Prints is comprised of our (i) custom built, compact, low-cost (85 USD), high-resolution (1,900 ppi), ergonomic fingerprint reader, and (ii) high-resolution infant fingerprint matcher. To evaluate the efficacy of Infant-Prints, we collected a longitudinal infant fingerprint database captured in 4 different sessions over a 12-month time span (December 2018 to January 2020), from 315 infants at the Saran Ashram Hospital, a charitable hospital in Dayalbagh, Agra, India. Our experimental results demonstrate, for the first time, that Infant-Prints can deliver accurate and reliable recognition (over time) of infants enrolled between the ages of 2-3 months, in time for effective delivery of vaccinations, healthcare, and nutritional supplements (TAR=95.2% @ FAR = 1.0% for infants aged 8-16 weeks at enrollment and authenticated 3 months later).
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Oct 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 1; 2025: 1; 2026: 2.
7 papers.
- 2021Biometrics: Trust, but Verifycited by 39
- 2024IFViT: Interpretable Fixed-Length Representation for Fingerprint Matching via Vision Transformercited by 16
- 2023Child Palm-ID: Contactless Palmprint Recognition for Childrencited by 2
- 2025An on-production high-resolution longitudinal neonatal fingerprint database in Brazilcited by 2
- 2026Recursive Class Connectivity Classification (R3C) Applied to Binary Image Segmentation for Improved Infant Fingerprint Enhancementcited by 1
- 2022Child PalmID: Contactless Palmprint Recognitioncited by 0
- 2026Infant Fingerprints: Quality Assessment & Recognitioncited by 0
- 2026Infant Fingerprints: Quality Assessment & Recognition14 Oct 2026
- 2026Recursive Class Connectivity Classification (R3C) Applied to Binary Image Segmentation for Improved Infant Fingerprint Enhancement25 May 2026
- 2025An on-production high-resolution longitudinal neonatal fingerprint database in Brazil27 Apr 2025
- 2024IFViT: Interpretable Fixed-Length Representation for Fingerprint Matching via Vision Transformer12 Apr 2024
- 2023Child Palm-ID: Contactless Palmprint Recognition for Children9 May 2023
- 2022Child PalmID: Contactless Palmprint Recognition14 Dec 2022
- 2021Biometrics: Trust, but Verify14 May 2021