Biometric Authentication System Using Reduced Feature Data
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Solution Overview
Problem
Large-scale 1:N biometric authentication systems face challenges in maintaining high precision while ensuring speediness, as they are prone to false acceptance errors and lengthy processing times due to the large amount of registered data, which existing technologies fail to adequately address.
Innovation Solution
The proposed system employs an authentication system that uses an input device, an image pickup device, an image processing section, a storage device, and a matching processing unit to generate and match reduced feature data, allowing for quick and precise authentication by rearranging registered data based on similarity and using multiple layers of data sizes to optimize matching efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If large-scale 1:N authentication is implemented with huge amount of registered data, then authentication coverage is improved, but processing time is prolonged
Solution Approach 1:
The patent segments the authentication process into two distinct stages: a first matching process that performs initial screening of registered data against input data, and a second matching process that performs detailed verification only on candidate data identified in the first stage. This segmentation divides the huge amount of registered data into multiple processing phases, allowing the system to handle large-scale authentication without proportionally increasing processing time.
Solution Approach 2:
The first matching process performs preliminary action by conducting an initial screening of all registered data before the second matching process. This preliminary step identifies candidate data that are likely matches, allowing the system to prepare and pre-process potential matches before detailed verification is required, thereby reducing the overall processing time for large-scale authentication.
2Adaptability or versatility
If large-scale 1:N authentication is implemented with huge amount of registered data, then authentication coverage is improved, but false acceptance ratio increases
Solution Approach 1:
The two-stage matching process segments the authentication verification into initial screening and detailed verification phases. The first matching process performs a broader initial screening, while the second matching process performs more stringent detailed verification on candidate data. This segmentation allows the system to maintain low false acceptance ratios by ensuring that only data passing both screening levels are accepted, even when handling large-scale registered data.
Solution Approach 2:
The system uses feedback from the first matching process to guide the second matching process. Candidate data identified in the first stage are fed into the second stage for detailed verification, and the results from the second stage provide feedback on the effectiveness of the matching criteria. This feedback mechanism allows the system to adjust and optimize matching parameters to maintain low false acceptance ratios across large-scale authentication operations.
3Productivity
If multiple layers of data sizes are used to optimize matching efficiency, then processing speed is improved, but data structure complexity increases
Solution Approach 1:
The patent segments registered data into multiple layers with different sizes and levels of detail. The first matching process operates on a first layer of data with a certain size, while the second matching process operates on a second layer with different characteristics. This segmentation of data into multiple layers allows the system to optimize processing speed by matching at appropriate levels of detail, while the structured approach to layering keeps data structure complexity manageable through clear organization and defined relationships between layers.
Data Source
AI summary
It is provided an authentication system comprising: an input device; an image pickup device for picking up an image of the living body; an image processing unit for processing the image picked up by the image pickup device; a storage device for storing a plurality of pieces of first feature data and a plurality of pieces of second feature data; and a matching processing unit for checking input data, which indicates features of a living body picked up by the image pickup device, against each of the plurality of pieces of first feature data and each of the plurality of pieces of second feature data. Each of the plurality of pieces of second feature data is data that is smaller in size than each of the plurality of pieces of first feature data and that includes at least a part of the features of the living body.