Fingerprint biometric analytical tool for intra-person identification
This technology is a fingerprint biometric analysis method to recognize fingerprints across different fingers from the same person.
Unmet Need: Analytical method that recognizes different fingerprints from the same person
Identification by fingerprint is routinely used as a tool for authentication security and crime forensics. While this method of biometric verification is often accurate and convenient, it is highly limited in that it is unable to match different fingers from the same person. This renders the technology useless in scenarios where the presented fingerprints are from different fingers than those on record.
The Technology: Feature correlations learning method to identify intra-person fingerprints
This technology demonstrates fingerprint recognition across different fingers from the same person. The technology utilizes deep encoders and machine learning to translate fingerprint images into data that can be analyzed for specific feature correlations. Neural networking is employed to verify that fingerprint feature correlations are not spontaneous and display a genuine pattern. The outcome of the technique is a score of how similar two fingerprints are and the confidence that they belong to the same person.
This technology has been validated with images of human fingerprints.
Applications:
- Digital authentication
- Forensic sciences
- Criminal prosecutions
- Background checks
- Biometric safety
- Mass disaster identification
- Employee identification
Advantages:
- Expands fingerprint analysis to enable identification of fingerprints from the same hand
- Provides scores of how similar two fingerprints are
- Provides confidence that two fingerprints belong to the same person
Lead Inventor:
Patent Information:
Patent Pending
Related Publications:
- Guo G, Ray A, Izydorczak M, Goldfeder J, Xu W. “Unveiling intra-person fingerprint similarity via deep contrastive learning” Science Advances. 2024 Jan 12; 10(2).
- Columbia Engineering article
Tech Ventures Reference:
- IR CU23306
- Licensing Contact: Dovina Qu