Fingerprint Sensor Calibration Using Statistical Range Detection
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Solution Overview
Problem
Current fingerprint recognition devices face errors and potential shutdowns during initial environmental calibration when a user's finger is present, as they cannot accurately distinguish between environmental interference and the user's fingerprint, leading to incorrect readings and calibration issues.
Innovation Solution
A fingerprint sensing device and calibration method that uses a processor to determine if a user's finger is on the sensor during initial calibration by comparing the sensed environment value to default and statistical ranges derived from various fingerprint data categories, allowing for precise calibration and accurate fingerprint pattern recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the fingerprint sensor performs initial environmental calibration when the device is started, then the environment value can be detected to reduce environmental interference, but if the user has put his/her finger on the sensor at this moment, errors will occur in the detection of the environment value
Solution Approach 1:
The patent applies preliminary action by performing environmental calibration before normal fingerprint recognition operations. The system detects environment values during initial startup when no fingerprint should be present, establishing a baseline for later comparison. This timing strategy ensures that calibration data is collected under known conditions (no finger on sensor), preventing contamination of calibration data with fingerprint signals.
Solution Approach 2:
The patent inverts the conventional approach by having the fingerprint sensor detect environment values (rather than just fingerprint data) during initial calibration. Instead of treating all sensor readings as fingerprint data, the system reverses the detection focus to measure environmental baseline first, then uses this inverted perspective to distinguish between environmental interference and actual fingerprint signals during subsequent operations.
2Object-affected harmful factors
If the fingerprint sensor detects environment values during initial calibration, then environmental interference can be reduced, but the device cannot determine whether the user's finger is on the sensor
Solution Approach 1:
The patent segments the sensor's detection function into two distinct modes: environmental detection mode during initial calibration, and fingerprint detection mode during normal operation. By dividing the detection process into these separate phases, the system can optimize for environmental baseline collection first, then switch to fingerprint recognition without confusion between the two detection objectives.
Solution Approach 2:
The patent introduces an intermediary comparison mechanism that uses the pre-collected environmental baseline as a reference mediator. When fingerprint recognition is performed, the system compares current sensor readings against the stored environmental baseline to identify and subtract environmental interference, thereby isolating the actual fingerprint signal from environmental noise.
3Reliability
If the environment value is not in the default environment range, the device performs calibration again or shuts down, but this causes loss of time and reduces productivity
Solution Approach 1:
The patent applies dynamics by making the calibration process adaptive rather than static. Instead of requiring environment values to match a fixed default range, the system dynamically adjusts the acceptable range based on actual environmental conditions detected during startup. If the environment value falls outside the default range, the system adapts by using the detected value as the new baseline, allowing calibration to proceed successfully without repeated retries or shutdowns.
Solution Approach 2:
The patent changes the parameter thresholds for acceptable environment values based on detected conditions. Rather than using a fixed default environment range, the system modifies the reference parameters dynamically - when an environment value outside the default range is detected, the system adjusts its calibration parameters to accommodate the actual environmental conditions, thereby maintaining calibration accuracy while avoiding repeated failures.
Data Source
AI summary
A fingerprint sensing device, an electronic device, and a calibration method for a fingerprint sensor are provided. The calibration method includes following steps: obtaining an initial environment value while the fingerprint sensor performs initial environmental calibration, and determining whether the initial environment value is in a default environment range or not; determining whether the initial environment value is in one of a plurality of statistical ranges when the initial environment value is not in the default environment range, wherein each of the statistical ranges is obtained statistically by a plurality of fingerprint data of one of a plurality of categories; and, when the initial environment value is in a target statistical range, calibrating the fingerprint sensor according to a target value and an environment default value, wherein the target value corresponds to the target statistical range, and the environment default value corresponds to the default environment range.