Fingerprint Pattern Registration Validation
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Solution Overview
Problem
Conventional pattern registration systems face challenges in identifying and preventing invalid or unauthorized patterns during the trusted mode registration process, particularly when the pattern capture area size is small, leading to compromised or degraded subsequent pattern identification, verification, and recognition systems.
Innovation Solution
A system and method that uses a pattern matcher to compare fingerprint patterns against a reference database, recording match results in a matrix and discarding non-matching patterns, with a threshold-based validation process to ensure only valid patterns are registered, allowing for dynamic addition of new patterns and continuous validation within the trusted mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems accept all submitted patterns during trusted mode registration, then registration process is simple and fast, but the reference database becomes compromised or degraded due to invalid or unauthorized patterns
Solution Approach 1:
The system performs preliminary validation of submitted patterns during the registration process by comparing them against existing reference patterns using a pattern matcher. This preliminary action identifies and flags potentially invalid or unauthorized patterns before they are added to the reference database, preventing database degradation while maintaining a structured registration workflow
Solution Approach 2:
The system implements feedback mechanisms where pattern matching results are analyzed and used to determine whether submitted patterns should be accepted or rejected. The feedback loop involves comparing submitted patterns against reference patterns, evaluating match quality, and using these results to make acceptance decisions, thereby maintaining database integrity through iterative validation
2Area of moving object
If the pattern capture area size is made smaller, then the sensor design becomes more compact, but it becomes more difficult to determine in real-time whether all captured patterns are from the same pattern source
Solution Approach 1:
The system replaces manual or complex mechanical verification methods with automated pattern matching algorithms. The pattern matcher computationally compares captured patterns against reference patterns to verify source consistency, eliminating the need for large capture areas or complex physical verification mechanisms while maintaining accurate source identification
Solution Approach 2:
The system changes the approach from relying on spatial parameters (large capture area) to using pattern recognition parameters (feature extraction and matching metrics). By analyzing pattern features, ridge characteristics, and matching scores rather than relying on capture area size, the system can verify source consistency even with small capture areas
Data Source
AI summary
A system, method, and computer program product for automatic machine-implemented pattern registration, particularly suited to small sensor systems which include a reduced image capture area size relative to the pattern being sensed.