Biometric Authentication Error Indication and Alignment Feedback
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Solution Overview
Problem
Existing biometric authentication techniques are cumbersome, often requiring precise alignment during enrollment and authentication, leading to false negatives and increased user effort, and rely solely on two-dimensional representations, neglecting three-dimensional characteristics, thus wasting time and energy, especially in battery-operated devices.
Innovation Solution
The development of efficient biometric authentication methods and interfaces that reduce cognitive burden, conserve power, and enhance user satisfaction by providing intuitive and efficient enrollment and authentication processes, utilizing three-dimensional biometric analysis and tactile feedback to guide users, such as through dynamic user interface swaps and error indication animations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precise alignment is required during biometric authentication, then measurement precision is improved, but ease of operation deteriorates and loss of time increases
Solution Approach 1:
The system provides real-time feedback to the user through visual indicators showing the degree of alignment achieved. The feedback mechanism guides users to adjust their position or the device angle until optimal alignment is reached, thereby maintaining high measurement precision while reducing user effort through intuitive guidance.
Solution Approach 2:
The system performs preliminary alignment assessment before final authentication processing. By pre-evaluating the alignment quality and providing corrective guidance in advance, the system prevents failed authentication attempts and reduces the need for repeated trials, thus improving ease of operation without sacrificing precision.
2Reliability
If multiple iterations of biometric authentication are performed, then reliability is improved, but loss of time increases and use of energy increases
Solution Approach 1:
The system performs preliminary quality assessment of the biometric capture during the first iteration. By evaluating alignment quality, illumination conditions, and signal strength before final authentication, the system can determine early whether a second iteration is necessary, thereby maintaining reliability while minimizing unnecessary time consumption.
Solution Approach 2:
The system automatically adjusts processing parameters and selects optimal authentication strategies based on real-time quality metrics without requiring user intervention. This self-service approach enables the system to quickly determine whether additional iterations are needed, reducing overall authentication time while maintaining high reliability through adaptive processing.
3Device complexity
If two-dimensional representation is used for biometric analysis, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system incorporates depth information and three-dimensional spatial characteristics into the biometric analysis by capturing elevation data, facial contour information, and spatial relationships between features. This dimensional enhancement improves measurement precision by providing additional geometric constraints while maintaining manageable device complexity through efficient 3D processing algorithms.
4Measurement precision
If extensive biometric processing is performed, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system performs preliminary quality assessment and preprocessing to identify high-value processing opportunities. By evaluating capture quality metrics before full authentication processing, the system can skip extensive processing for low-quality captures and focus computational resources only on promising candidates, thereby maintaining precision while reducing overall energy consumption.
Solution Approach 2:
The system applies processing at varying levels of intensity based on real-time quality metrics. For high-quality captures, full processing is applied to ensure maximum precision. For marginal captures, reduced processing is performed initially, with full processing applied only if needed, thus optimizing the balance between measurement precision and energy consumption.
Data Source
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AI summary
The present disclosure relates generally to implementing biometric authentication, including providing user interfaces for: a biometric enrollment process tutorial, aligning a biometric feature for enrollment, enrolling a biometric feature, providing hints during a biometric enrollment process, application-based biometric authentication, autofilling biometrically secured fields, unlocking a device using biometric authentication, retrying biometric authentication, managing transfers using biometric authentication, interstitial user interfaces during biometric authentication, preventing retrying biometric authentication, cached biometric authentication, autofilling fillable fields based on visibility criteria, automatic log-in using biometric authentication, retrying biometric authentication at a credential entry user interface, providing indications of error conditions during biometric authentication, providing indications about the biometric sensor during biometric authentication, and orienting the device to enroll a biometric feature.