Fingerprint Image Reconstruction via Sequence Correlation
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Solution Overview
Problem
Fingerprint recognition devices face issues with inadequate resolution, partial imaging, improper orientation, and noise interference, which can lead to impaired enrollment and recognition of fingerprint images.
Innovation Solution
The method involves correlating sequences of fingerprint images to construct a unified, high-quality image by selecting superior frames, removing noise through filtering, and providing user feedback for optimal image capture, including orientation and pressure guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the user's finger is positioned too far from the fingerprint recognition device or exerts too much pressure, then the fingerprint image may have inadequate resolution or be too blurry, but the device structure remains simple
Solution Approach 1:
The system captures multiple fingerprint images in sequence and provides feedback to the user about image quality metrics (completeness, resolution, orientation). Based on this feedback, the system guides the user to adjust finger positioning, pressure, and orientation until optimal image quality is achieved, thereby resolving the contradiction between measurement precision and ease of operation.
Solution Approach 2:
The system performs preliminary capture of multiple fingerprint images before final processing. By capturing a sequence of images and selecting the best quality frames in advance, the system ensures high resolution without requiring the user to perfectly position their finger on the first attempt.
2Loss of information
If the user's finger is positioned with only part of the finger in proper position, then only a partial fingerprint image is collected, but the sensing area coverage is reduced
Solution Approach 1:
The system merges multiple partial fingerprint images captured in sequence into a single complete fingerprint image. By correlating and combining information from multiple images taken at different positions or orientations, the system reconstructs the complete fingerprint pattern, thereby resolving the contradiction between information completeness and sensing area coverage.
3Reliability
If the fingerprint image is collected with noise from ambient electromagnetic noise, circuitry noise, or particulate matter, then the quality of the fingerprint image is altered, but the device complexity remains low
Solution Approach 1:
The system continuously captures multiple fingerprint images in sequence rather than relying on a single image. This continuous capture allows the system to accumulate sufficient signal data that overcomes random noise through statistical processing, thereby improving reliability without requiring complex hardware noise filtering.
Solution Approach 2:
The system extracts the useful fingerprint signal from noisy images by capturing multiple images and processing them to separate the consistent fingerprint pattern from random noise. Through correlation and averaging of multiple images, the true fingerprint information is extracted while noise is eliminated.
4Reliability
If multiple fingerprint images are captured to improve quality, then the reliability of fingerprint enrollment is improved, but the time required for enrollment increases
Solution Approach 1:
The system captures more images than strictly necessary (excessive action) to ensure high reliability, but uses efficient processing to select only the best quality frames for final enrollment. This approach ensures reliability while minimizing the actual processing time by not requiring all captured images to be processed.
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 enhances the reliability and quality of fingerprint images, improving enrollment and recognition processes by aggregating partial images and reducing noise, thus ensuring accurate biometric data collection.
Implementation Method 1
capacitive sensing allows a fingerprint recognition device to determine the ridges and valleys of the user's finger, in response to relative capacitances measured between the user's finger (such as on the epidermis of the user's finger) and a capacitive plate in the fingerprint recognition device
Data Source
AI summary
A sequence of biometric data images is received, such as, for example, a sequence of fingerprint images, and a set of biometric data images is selected from the sequence of images. The set of images can include one or more segments of at least one image in the sequence of images. One or more portions of at least one image of biometric data in the set of images can be selected to be included in the unified image of biometric data. The unified image of biometric data can be constructed using the one or more portions of the at least one image of biometric data. If the unified image of biometric data is not complete, a user can be prompted for one or more additional images of biometric data.