Pay By Showing Your Palm: A Study of Palmprint Verification on Mobile Platforms
Abstract
With the fast development of smart mobile devices, mobile phones have gradually become an indispensable part of people's lives. Many biometric technologies based on mobile platforms have also developed rapidly, such as face verification and fingerprint recognition. However, the great potential of palmprint has been neglected. In this paper, we conducted a thorough study of palmprint verification on mobile devices for the first time. Firstly, we established an annotated, palmprint dataset named MPD, which was collected by multi-brands phones in two different sessions. As the largest dataset in this field, MPD contains 16,000 palm images from 200 subjects. Secondly, we built a DCNN-based palmprint verification system named DeepMPV for mobile platforms. The efficiency and performance of our system have been corroborated on our collected dataset. The labelled dataset and the source code are publicly available at https://cslinzhang.github.io/deepmpv/.
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A DCNN-based palmprint verification system named DeepMPV is proposed for mobile payment.
“Besides, a DCNN-based palmprint verification system named DeepMPV is proposed for mobile payment in [104].”
From Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things (2021) · cites this paper as [104]
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- Authors
- Zhang, Y., Zhang, L., Liu, X., Zhao, S., Shen, Y., & Yang, Y.
- Affiliations
- Tongji University (CN)
- Uppsala University (SE)
- Venue
- 2019 IEEE International Conference on Multimedia and Expo (ICME)
- Publisher
- IEEE
- Published
- 2019-07
- Pages
- 862-867
- OpenAlex
- W2965109540
- Cited by
- 25
- References
- 17
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 4 · 2023: 4 · 2022: 5 · 2020: 4
- FWCI
- 1.73
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE International Conference on Multimedia and Expo (ICME) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
- Physical Sciences › Computer Science › Information Systems › User Authentication and Security Systems
- Physical Sciences › Engineering › Biomedical Engineering › Gait Recognition and Analysis
- Keywords
- palmprint verification, palmprint recognition, mobile biometrics, mobile devices, deep convolutional neural networks, biometric authentication
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