Fingerprint Unlocking Parameter Adjustment for Moisture Variations
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Solution Overview
Problem
Fingerprint unlocking efficiency is reduced when fingers are over-dry or over-wet, requiring multiple attempts to successfully unlock a terminal due to suboptimal fingerprint recognition.
Innovation Solution
A method that determines the number of target feature points in a fingerprint image, adjusts parameters based on a preset mapping relationship, and receives a second fingerprint image to improve matching efficiency with a preset template, thereby enhancing unlocking speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional fingerprint recognition is used without parameter adjustment, then the system is simple to operate, but unlocking efficiency decreases when finger moisture is abnormal (over-dry or over-wet)
Solution Approach 1:
The system performs preliminary analysis on the first fingerprint image to determine feature point quantity and classify finger moisture status before actual recognition. This preliminary action allows the system to adjust parameters in advance, ensuring high unlocking efficiency even when finger moisture is abnormal, without requiring complex real-time adjustments during the recognition process
Solution Approach 2:
The system dynamically adjusts the second fingerprint image acquisition parameters based on the classified finger moisture status. Different acquisition parameters are applied for different moisture conditions, making the system adaptable to varying finger states while maintaining a relatively simple overall structure through parameter-based differentiation
2Loss of time
If multiple fingerprint attempts are required for abnormal moisture conditions, then system complexity remains low, but time consumption increases
Solution Approach 1:
The system performs preliminary classification of finger moisture status using the first fingerprint image before the user needs to make multiple attempts. This preliminary action identifies abnormal moisture conditions early, allowing the system to switch to optimized acquisition parameters for the second fingerprint image, thereby reducing the time loss from multiple attempts and improving overall unlocking efficiency
Solution Approach 2:
The system uses feedback from the first fingerprint image analysis (feature point quantity and moisture classification) to adjust the acquisition parameters for the second fingerprint image. This feedback mechanism ensures that the system adapts to abnormal moisture conditions efficiently, reducing unnecessary repeated attempts and minimizing time loss
Data Source
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AI summary
A fingerprint unlocking method may include receiving a first fingerprint image. The number of target feature points of the first fingerprint image is determined. A target adjustment parameter corresponding to the number of target feature points is acquired according to a preset mapping relation between the number of feature points and adjustment parameters. A second fingerprint image is received according to the target adjustment parameter. A terminal is unlocked when the second fingerprint image matches with a preset fingerprint template. A terminal is also provided.