mlsanityData to 7 Oct 2026

Mobile Touchless Fingerprint Recognition: Implementation, Performance and Usability Aspects

arXiv 2103.03038 ↗First posted 4 Mar 2021cs.CVcited by 10

Not on the map. Why?

Abstract (arXiv)

This work presents an automated touchless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition pipeline and discuss important requirements for a fully automated capturing system. Also, our implementation is made publicly available for research purposes. During a database acquisition, a total number of 1,360 touchless and touch-based samples of 29 subjects are captured in two different environmental situations. Experiments on the acquired database show a comparable performance of our touchless scheme and the touch-based baseline scheme under constrained environmental influences. A comparative usability study on both capturing device types indicates that the majority of subjects prefer the touchless capturing method. Based on our experimental results we analyze the impact of the current COVID-19 pandemic on fingerprint recognition systems. Finally, implementation aspects of touchless fingerprint recognition are summarized.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 3 of its 44 references that are in the map. First posted on arXiv 4 Mar 2021.

Builds on

3 of 44 references.

References · 3

  1. 2017FingerNet: An Unified Deep Network for Fingerprint Minutiae Extractioncited by 36
  2. 2018Matching Fingerphotos to Slap Fingerprint Imagescited by 8
  3. 2019A Collaborative Approach using Ridge-Valley Minutiae for More Accurate Contactless Fingerprint Identificationcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 3; 2023: 2; 2024: 0; 2025: 2; 2026: 1.

10 papers.