Partial Fingerprint Scanner Edge Resolution via Motion Extrapolation
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Solution Overview
Problem
Partial fingerprint scanners face challenges in accurately capturing fingerprint data near the edges of a swipe due to inadequate finger position and motion data, leading to incomplete and noisy readings, which results in discarded data and suboptimal pattern recognition performance.
Innovation Solution
The method employs extrapolation of finger motion parameters and image analysis to determine the probable position and boundaries of the fingertip, combining these with processed partial fingerprint images to correct for inaccurate data and reject non-fingerprint data, thereby enhancing the completeness and accuracy of the fingerprint image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If partial fingerprint scanning is used to reduce sensor size and cost, then device size and cost are reduced, but measurement precision deteriorates at fingerprint edges
Solution Approach 1:
The system performs preliminary actions by capturing multiple overlapping partial fingerprint images during a swipe motion before final image reconstruction. This allows the system to gather sufficient data from edge regions that would otherwise be missed, compensating for the limited sensing area through proactive data collection during the scanning process.
Solution Approach 2:
The patent transitions from static 2D fingerprint capture to dynamic 3D spatiotemporal data collection by incorporating the time dimension during swipe motion. Multiple partial images are captured at different positions and times, then reconstructed into a complete fingerprint image, effectively using temporal dimension to compensate for spatial limitations of the small sensor.
2Productivity
If finger position data is used to track swipe motion, then image assembly is improved, but data reliability deteriorates at swipe edges
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring finger position during the swipe and using this information to guide the image assembly process. The reconstructed fingerprint image is compared with expected patterns, and adjustments are made to compensate for position tracking errors, particularly at the edges where reliability is lowest.
Solution Approach 2:
The system performs preliminary calibration and validation of finger position data before final image reconstruction. By anticipating potential data reliability issues at swipe edges, the system prepares correction algorithms in advance and uses multiple redundant measurements to ensure accurate image assembly despite position tracking limitations.
3Measurement precision
If edge data is discarded due to noise and incompleteness, then pattern recognition accuracy is maintained, but information loss increases
Solution Approach 1:
The system appears to discard noisy edge data during initial processing but then recovers this information through advanced image reconstruction algorithms. By using multiple overlapping partial images and sophisticated assembly techniques, the system retrieves valuable fingerprint edge information that would otherwise be lost, maintaining both accuracy and information completeness.
Solution Approach 2:
The system performs preliminary noise filtering and data validation before final image reconstruction, identifying potentially useful edge data that meets certain quality thresholds. This preliminary sorting allows the system to retain valuable information while discarding only truly noisy data, optimizing the balance between accuracy and information retention.
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 allows for more complete and accurate fingerprint data capture, including edges, improving pattern recognition and reducing mismatches by incorporating previously discarded data, resulting in superior fingerprint analysis and verification.
Implementation Method 1
The electrodes are electrically excited in a progressive scan pattern and the ridges and valleys of a finger pad alter the electrical properties (usually the capacitive properties) of the excitation electrode—sensing electrode interaction, and this in turn creates a detectable electrical signal.
Implementation Method 2
These devices create sensing elements by creating a linear array composed of many miniature excitation electrodes, spaced at a high density, such as a density of approximately 500 electrodes per inch. The tips of these electrodes are separated from a single sensing electrode by a small sensor gap.
Data Source
AI summary
A fingerprint analysis method for partial fingerprint scanners that has an improved ability to resolve fingerprints from the tips of fingers, as well as an improved ability to cope with suboptimal finger swipes. The method uses various extrapolation methods to more accurately determine the position of a scanned fingertip is as the tip of the finger passes a partial fingerprint scanner. The method also monitors the image characteristics of the partial fingerprint image returned by the partial fingerprint scanner, and uses these image characteristics to determine exactly where the image of the fingertip itself is lost, and imaging of non-fingerprint data begins. By combining the most probable fingertip position as a function of time data obtained from extrapolated finger motion data, with image analyzed fingerprint images more precisely determined to be near the fingertip edges, superior fingerprint images extending closer to the edge of the fingerprint may be obtained.