Biometric Identification Database Segmentation for Throughput
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Solution Overview
Problem
Biometric identification systems face delays due to the time-consuming comparison of biometric data, particularly as the database size increases, leading to bottlenecks and increased costs when addressing this with more hardware or additional capture devices.
Innovation Solution
The method divides user biometric data into two groups, with a rapid comparison for regular users and a more precise comparison for non-regular users, allowing for transparent allocation without user intervention and periodic adjustment based on validated identifications to prioritize regular users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of biometric capture devices and gates is increased to reduce identification delays, then the identification throughput is improved, but the hardware cost and space requirements increase
Solution Approach 1:
The patent segments the database into two distinct groups: a first group containing biometric data of frequent users and a second group containing biometric data of infrequent users. This segmentation allows the system to perform rapid comparisons against the smaller first group for most users, while only performing exhaustive comparisons against the larger second group when necessary, thereby reducing average identification time without requiring additional hardware
Solution Approach 2:
The patent applies different comparison strategies to different user groups based on their access patterns. For users in the first group (frequent users), the system performs rapid comparisons optimized for speed. For users in the second group (infrequent users), the system performs more thorough comparisons. This local differentiation of processing quality allows the system to optimize for speed where appropriate while maintaining security where needed, improving overall throughput without proportional hardware increases
2Loss of time
If the power of the computing means is increased to speed up biometric data comparison, then the identification time is reduced, but the cost increases
Solution Approach 1:
The patent segments the comparison process into two phases: a first rapid comparison phase against the first group of biometric data, and a second exhaustive comparison phase against the second group. This segmentation allows the system to achieve fast identification for frequent users through the optimized first phase, reducing the need for expensive high-power computing infrastructure while maintaining security through the second phase when needed
Solution Approach 2:
The patent applies partial action by performing a simplified rapid comparison against the first group rather than performing a complete comparison against the entire database. This partial comparison is sufficient for frequent users and provides a quick filter, reducing the computational burden and allowing standard computing hardware to achieve high-speed identification without requiring expensive upgrades
3Productivity
If the database is divided into two groups requiring user input of group allocation, then the comparison efficiency is improved, but the ease of operation decreases due to additional user interaction requirements
Solution Approach 1:
The patent implements self-service by automatically allocating users to the appropriate group based on their access frequency history stored in the database. The system autonomously determines whether a user belongs to the first group (frequent users) or the second group (infrequent users) without requiring any user input or awareness of the grouping mechanism. This maintains ease of operation while achieving the productivity benefits of segmented comparison
Solution Approach 2:
The patent uses feedback from historical access patterns to dynamically manage group allocation. The system monitors and stores the frequency of user accesses, using this feedback information to automatically classify users into appropriate groups. This feedback mechanism allows the system to adapt to changing usage patterns while maintaining automatic, transparent operation without user intervention
Data Source
AI summary
Identification method using data in a database that are distributed in at least a first group of data and a second group of data, a comparison being made using first of all the biometric data in the first group and then, in the event of failure of the comparison, using the biometric data in the second group, the distribution of the data between the groups being modified according to a number of validated identifications stored for each user, the first group comprising the data of the user comprising a number of validated identifications greater than a predetermined threshold over a predetermined period and identification system for implementing this method.