Biometric Verification Using Non-Visible Light Edge Capture
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Solution Overview
Problem
Traditional identity verification methods, such as key-based and biometric systems, face challenges in ensuring accurate access control due to issues like key duplication, environmental limitations, and high false acceptance/false rejection rates, particularly in varying light conditions and population similarity.
Innovation Solution
A system utilizing an edge capture device that emits non-visible light, detects reflected and radiated light, and generates a biometric template by analyzing sampling points with characteristic values, macroblocks, and weighted values to enhance facial recognition accuracy and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional biometric sensors are used for facial recognition, then identity verification can be performed, but the system performance is compromised in direct sunlight due to glares, shadows, and other artifacts
Solution Approach 1:
The patent introduces an intermediary light source (infrared or other non-visible light) between the subject and the sensor to illuminate the subject's features. This intermediary lighting system allows the sensor to capture facial features without being affected by ambient lighting conditions such as sunlight, glares, or shadows, thereby maintaining verification reliability across varying environmental conditions.
2Measurement precision
If traditional biometric sensors are used, then facial features can be captured, but motion blur, insufficient resolution, and camera angles obscure subject details making heterogeneous facial recognition difficult
Solution Approach 1:
The patent changes the parameter of light wavelength from visible light to non-visible light (such as infrared). This parameter change allows the sensor to capture facial features with higher precision without being affected by motion blur, resolution limitations, or angular variations, as non-visible light can penetrate through some obstructions and provide more stable feature detection.
3Ease of operation
If conventional key-based access control is used, then access can be granted to authorized requesters, but it is very difficult to determine if the person holding the key is the actual authorized requester
Solution Approach 1:
The patent replaces the mechanical key-based access control system with a biometric recognition system using non-visible light sensing. Instead of relying on physical objects (keys) that can be stolen or duplicated, the system uses optical sensing to capture and verify unique facial features, thereby maintaining ease of operation while significantly improving identity verification accuracy and reliability.
4Adaptability or versatility
If biometric sensors operate in varying light conditions, then broader environmental applicability is achieved, but false acceptance and false recognition rates increase
Solution Approach 1:
The patent employs a dynamic lighting system that actively controls the illumination conditions for each biometric measurement. The system can adjust the intensity, wavelength, and direction of the non-visible light source based on environmental conditions, ensuring optimal measurement precision across varying ambient lighting conditions while maintaining high adaptability to different environments.
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
The system provides robust and reliable identity verification with reduced false positives/negatives, capable of functioning across varying light conditions and population sizes, offering improved security and accuracy in access control.
Implementation Method 1
A system utilizing an edge capture device that emits non-visible light, detects reflected and radiated light
Implementation Method 2
detects reflected and radiated light
Data Source
AI summary
Aspects of the present disclosure include methods for generating a sampled profile including a plurality of sampling points having a plurality of characteristic values associated with the detected non-visible light, identifying one or more macroblocks each includes a subset of the plurality of sampling points, calculating a number of occurrences of the local pattern value within each subset of the plurality of the sampling points for each of the one or more macroblocks, generating a first array including a plurality of weighted values by calculating the plurality of weighted values based on the numbers of occurrences of the local pattern value and corresponding sizes of the one or more macroblocks, assigning a unique index to each of the plurality of weighted values, generating a second array of the unique index by ranking the plurality of weighted values, and generating a third array including a plurality of ranking distances.