Biometric Sensor Authenticity Alleviation via Multi-Modal Fusion
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Solution Overview
Problem
Existing biometric authentication systems face challenges in accurately detecting fingerprints due to variations in sensor types, finger shapes, environmental factors like temperature, and sensor interface issues, leading to false identifications and errors.
Innovation Solution
A method and system that receive fingerprint data from multiple sensors, extract attributes, determine expanded values using predefined techniques, train a model for authentication, predict errors over time, and retrain the model to alleviate authenticity issues, reducing dependency on sensor type and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical diodes are used as sensors to capture high-resolution optical photographs of fingerprints, then the resolution and detail of fingerprint capture is improved, but the system becomes vulnerable to fraud through similar user images and cannot sense external factors
Solution Approach 1:
The patent combines multiple sensor types (optical sensors, thermal sensors, capacitive sensors) into a single authentication system. This merging allows the system to capture both high-resolution optical images and external environmental factors simultaneously, resolving the contradiction between resolution and security by making fraud detection multi-dimensional
Solution Approach 2:
The patent introduces an intermediary layer of environmental factor sensing that mediates between the optical capture and authentication decision. This intermediary thermal/capacitive sensing layer provides additional verification that distinguishes real fingerprints from fraudulent images, maintaining high resolution while improving security
2Device complexity
If a single type of hardware sensor is used for fingerprint detection, then the system complexity is reduced, but the accuracy deteriorates due to variations in finger shapes, sizes, moisture, and environmental conditions
Solution Approach 1:
The patent creates a universal authentication system that can handle multiple sensor types and environmental conditions through a common processing framework. The system is designed to work with optical, thermal, and capacitive sensors interchangeably, making it universally applicable while maintaining high accuracy across diverse conditions
Solution Approach 2:
The patent dynamically adjusts detection parameters based on environmental conditions and sensor type. By changing parameters such as temperature thresholds, moisture levels, and pressure sensitivity according to the specific sensor and environmental context, the system maintains high accuracy without requiring separate specialized systems for each condition
3Device complexity
If fingerprint detection systems do not account for external environmental factors like temperature, then the device complexity is reduced, but errors occur due to improper temperature ratios and wet hand conditions
Solution Approach 1:
The patent performs preliminary environmental assessment by measuring temperature, humidity, and other environmental factors before the actual fingerprint detection. This preliminary action allows the system to pre-adjust detection parameters and alert users to suboptimal conditions, improving reliability without adding significant complexity to the core detection mechanism
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a robust authentication system with reduced execution time and increased accuracy by learning and adapting to errors, independent of sensor type and environmental factors, enhancing user experience and security.
Implementation Method 1
optical diodes as sensors to capture high-resolution optical photographs of the fingerprint. In such scenario, optical diode light reflection caused by the finger pours represent biometric patterns
Implementation Method 2
thermal sensor and associated software models... The sensor need to be calibrated to detect the temperature changes and also to compensate the error caused by temperature variation
Implementation Method 3
capacitive sensors... usage has been limited due to breaching problem in this type of chipset
Data Source
AI summary
A method and authentication system for alleviating authenticity of sensors in biometric authentication is disclosed. The authentication system receives fingerprint data from a plurality of sensing devices configured in the authentication system and extract one or more attributes associated with the fingerprint data. An expanded value for each of the one or more attributes is determined based on one or more predefined techniques. The authentication system (101) trains a model associated with authentication of fingerprints using the one or more attributes and corresponding expanded value. Further, one or more errors associated with the fingerprint data are predicted based on fingerprint data received over a period of time in real-time and the model is retrained based on the predicted one or more errors to alleviate authenticity of sensors in biometric authentication.