Biometric Authentication Using Base Station Location Filtering
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Solution Overview
Problem
Current 1:N face recognition technologies face challenges in open environments due to reduced accuracy and user experience issues, such as requiring additional user operations and the need for Bluetooth functionality, especially in high-traffic scenarios with large face data databases.
Innovation Solution
A biometric-based identity authentication method and system that generates and compares mobile terminal number lists based on user biometrics and pre-established binding relationships, allowing for accurate identity authentication without the need for additional user operations or Bluetooth functionality, by using a base station to gather mobile terminal numbers and a biometric recognition background to narrow down the recognition range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 1:N face recognition is applied in open environments with large face data databases, then the recognition range is expanded, but the recognition accuracy drops significantly
Solution Approach 1:
The patent segments the large-scale 1:N recognition problem into two stages: first using base station location data to narrow down the search range to a local area, then performing biometric verification within this reduced range. This segmentation resolves the contradiction by maintaining broad adaptability while improving accuracy through localized processing.
Solution Approach 2:
The patent introduces base station location information as an intermediary factor to bridge the gap between broad recognition range and high accuracy. The location data acts as a mediator that filters and prioritizes potential matches, enabling accurate recognition in open environments without requiring the user to manually narrow the search range.
2Measurement precision
If auxiliary methods are used to narrow down the recognition range, then the recognition accuracy is improved, but the user experience is degraded due to additional user operations
Solution Approach 1:
The patent implements self-service by automatically using the base station's existing location data to narrow down the recognition range without requiring any additional user actions. The system leverages data already collected during normal network communication, eliminating the need for users to manually provide location information or perform additional operations while maintaining high recognition accuracy.
3Measurement precision
If Bluetooth function is used to narrow down the recognition range, then the recognition accuracy is improved, but the ease of operation is degraded due to requiring user to turn on Bluetooth
Solution Approach 1:
The patent uses base station location information as an intermediary alternative to Bluetooth technology. This intermediary approach achieves the same goal of narrowing down the recognition range without requiring additional user operations, as the location data is automatically obtained through standard mobile network communication rather than requiring users to enable Bluetooth functionality.
4Adaptability or versatility
If edge device nodes are constructed to store facial features according to historical location, then the recognition range is narrowed down, but the device complexity increases and recognition accuracy is reduced
Solution Approach 1:
The patent extracts the location-based filtering function from complex edge device nodes and integrates it into the existing base station infrastructure. By using the base station's inherent location identification capabilities rather than constructing dedicated edge devices, the system achieves range narrowing without the additional complexity and cost of specialized hardware infrastructure.
Data Source
AI summary
The present invention relates to a biometric-based identity authentication method and system. The method includes: obtaining mobile terminal numbers of all users entering a specified area through a base station associated with the specified area which the users enter to generate a first mobile terminal number list; recognizing biometrics of users, and obtaining a second mobile terminal number list composed of n mobile terminal numbers with the highest similarity to the biometrics based on a pre-established binding relationship between biometrics of users and the mobile terminal numbers; and comparing the first mobile terminal number list with the second mobile terminal number list, wherein on the condition that the intersection of the two is one mobile terminal number, it is determined that the user of the mobile terminal number is the user with successful identity authentication, and on the condition that the intersection of the two is more than one number, it is determined that the user of the mobile terminal number with the highest biometric similarity in the intersection is the user with successful identity authentication. According to the present invention, the range of face recognition N can be narrowed down, and a user only needs to carry a mobile phone and 1:N face recognition can be completed without additional operations.