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ZJUT-EIFD: A Synchronously Collected External and Internal Fingerprint Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
|November 28, 2023
Summary
This study introduces ZJUT-EIFD, a novel database combining external fingerprints (EFs) and internal fingerprints (IFs) from optical coherence tomography (OCT). This resource addresses the need for research into IFs and EF-IF interoperability, enhancing fingerprint recognition security.
Area of Science:
- Biometrics
- Computer Science
- Medical Imaging
Background:
- External fingerprints (EFs) are susceptible to spoofing and environmental factors.
- Internal fingerprints (IFs) using optical coherence tomography (OCT) offer enhanced security but lack extensive research and public datasets.
- A gap exists in understanding and applying EF-IF interoperability.
Purpose of the Study:
- To introduce ZJUT-EIFD, the first public database integrating OCT-based IFs and traditional EFs.
- To provide a benchmark for evaluating IFs and EF-IF interoperability.
- To promote advancements in fingerprint recognition technology.
Main Methods:
- Developed ZJUT-EIFD database with synchronous acquisition of EFs and IFs using OCT and total internal reflection (TIR).
- Collected data from 399 fingers across 60 subjects.
- Detailed database composition, data quality, and verification performance.
Main Results:
- ZJUT-EIFD is the first public database to combine OCT and TIR for synchronous fingerprint acquisition.
- The database provides comprehensive data on both EFs and IFs.
- Initial analysis details data quality and verification performance.
Conclusions:
- ZJUT-EIFD serves as a crucial resource for EF-IF research and development.
- The database facilitates benchmarking and interoperability testing.
- This work is expected to significantly advance the field of fingerprint recognition.
