Biometric Identity Enrolment via Multi-Source Matching
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Solution Overview
Problem
The manual enrollment of biometric signatures into biometric systems is costly and time-consuming, especially for large organizations, as it requires human operators and can be prone to fraud when using secondary verification instruments.
Innovation Solution
A computer-implemented method that automatically associates a second biometric identifier with existing records in a datastore by comparing received biometric identifiers to identify a candidate matching record, eliminating the need for secondary verification instruments and enhancing the accuracy through multiple instances and fusion of biometric data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual enrollment is used to associate biometric identifiers with records, then accuracy of association can be ensured through human verification, but cost and time consumption increase significantly
Solution Approach 1:
The system enables self-service enrollment by automatically comparing biometric identifiers against existing records using algorithmic matching. The computer system autonomously performs the association task that previously required human operators, thereby increasing enrollment speed while maintaining accuracy through structured comparison protocols and confidence threshold evaluation.
2Reliability
If secondary verification instruments like cards or PINs are used to link biometric data, then fraud can be detected, but the enrollment process becomes more complex and vulnerable to instrument theft
Solution Approach 1:
The patent extracts and eliminates the dependency on secondary verification instruments such as cards or PINs from the enrollment process. By using purely biometric identifier comparison against existing records, the system removes the fraudulent verification layer while simplifying the overall process. The biometric data itself becomes the sole verification mechanism, reducing complexity and eliminating instrument theft vulnerabilities.
3Measurement precision
If multiple biometric identifiers are collected and compared to improve matching accuracy, then association precision increases, but processing time and computational resources increase
Solution Approach 1:
The system implements a staged comparison approach where biometric identifiers are processed in sequences of increasing scope. Initially, comparisons are performed against a subset of records or using simplified matching criteria, then progressively expanded to full database searches with more comprehensive biometric features. This allows the system to achieve high accuracy through multiple identifier comparisons while managing processing time through incremental refinement rather than exhaustive simultaneous processing.
Data Source
AI summary
Biometric computer systems are systems which use one or biometric identifiers to enroll, verify or identify a person. This disclosure concerns the automatic enrolment of people into biometric systems. Aspects include methods, computer systems, software and biometric systems. A first biometric identifier (i.e. face) and a second biometric identifier (e.g. iris) is captured (201). The first biometric identifier (e.g. face) is compared (206) to the biometric identifiers associated with records in the datastore (i.e. employment records 121) to identify a candidate matching record. An association of the second biometric identifier with the candidate record to be stored (209) in memory.