Biometric Authentication Fusion for Accuracy
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Solution Overview
Problem
Conventional identity authentication systems based on single biological characteristics, such as fingerprints, face recognition, or voice, face challenges in ensuring security and accuracy, especially when the quality of collected biological data is low, which is a concern in high-security environments like banks where high-quality fingerprint information of 5% of the population cannot be collected and existing technologies do not address the security and accuracy requirements effectively.
Innovation Solution
A method and device for authenticating identities using the fusion of multiple biological characteristics, including face, fingerprint, and voice, through characteristic extraction, normalization, dynamic weighting fusion, and Bayesian decision models to improve identification accuracy by combining multiple types of biological data, even when some data is of low quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single biological characteristic authentication is used, then device complexity is reduced, but identification accuracy and security deteriorate
Solution Approach 1:
The patent combines multiple biological characteristic authentication methods (fingerprint, facial recognition, iris recognition, voice recognition) into a unified authentication system. The system collects biological data from multiple sensors, processes each type of data through dedicated processing modules, and integrates the results to make a final authentication decision, thereby improving identification accuracy while maintaining manageable system complexity through modular design
2Measurement precision
If multiple biological characteristics are collected, then identification accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the authentication system into independent functional modules: data collection modules for different biological characteristics (fingerprint sensor, camera for facial recognition, iris scanner, microphone for voice recognition), separate processing modules for each characteristic type, and a fusion module that integrates results. This segmentation allows the system to handle multiple biological characteristics while keeping each component relatively simple and manageable
Solution Approach 2:
The patent designs a universal authentication framework that can handle multiple types of biological characteristics through a common processing architecture. The system uses a unified data structure and processing pipeline that can accommodate different sensor types and characteristic types, reducing overall system complexity despite supporting multiple authentication methods
3Adaptability or versatility
If normalization processing is applied to characteristic matrixes, then data compatibility is improved, but processing time increases
Solution Approach 1:
The patent performs normalization processing on biological characteristic data during the data collection and initial processing phase, before the actual authentication decision is made. By pre-normalizing the characteristic matrixes from different biological characteristics (fingerprint, facial recognition, iris, voice), the system ensures data compatibility is established early, allowing faster subsequent processing and decision-making without repeated normalization operations
Data Source
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AI summary
Disclosed in an embodiment of the present invention is a method for authenticating identify by means of fusion of multiple biological characteristics, which allows identity authentication to be carried out by using more than two types of biological characteristic identity information, thereby providing a higher identification accuracy. The method in the embodiment of the present invention comprises: collecting at least two types of biological characteristic identity information of a user to be identified; carrying out characteristic extraction on the at least two types of collected biological characteristic identity information, so as to obtain corresponding characteristic information; establishing characteristic matrixes according to the characteristic information, the biological characteristic identity information, the characteristic information and the characteristic matrixes being in a one-to-one correspondence; respectively carrying out normalization processing on all the characteristic matrixes; carrying out dynamic weighting fusion on all the normalized characteristic matrixes, so as to obtain a fused characteristic matrix; carrying out matching according to the fused characteristic matrix and a preset corresponding standard matrix, so as to obtain a corresponding matching score; and obtaining an identity identification result of the user to be identified according to a Bayesian decision model and the matching score. An embodiment of the present invention also provides a device for authenticating identify by means of fusion of multiple biological characteristics.