Fingerprint Sensor Minimum Sensing Area Processing
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Solution Overview
Problem
Existing fingerprint recognition technologies require a significant sensing area for accurate identification, which is not feasible in miniaturized devices, necessitating a method to extract and utilize feature information from a minimum fingerprint sensing area for enhanced user convenience and reduced non-display regions.
Innovation Solution
A fingerprint information processing method that acquires a fingerprint image from a minimum sensing area by calculating intensity variation values, selecting feature points, applying artificial distortion for noise filtering, and comparing intensity variation vectors for identification, allowing for accurate fingerprint registration and identification even with a reduced sensing area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large fingerprint sensing area is used to acquire sufficient fingerprint image data, then fingerprint identification accuracy is improved, but the non-display region area increases
Solution Approach 1:
The patent extracts only the essential feature information (intensity variation values) from the fingerprint image rather than using the entire fingerprint image data. This extraction approach allows accurate identification using minimal sensing area, resolving the contradiction between accuracy and area.
Solution Approach 2:
The patent applies artificial distortion specifically to regions containing feature point candidates and their neighboring pixels for noise filtering, rather than processing the entire image uniformly. This localized processing enables accurate feature extraction from minimal sensing areas.
2Area of stationary object
If the sensing area is minimized to reduce non-display region, then device compactness is improved, but fingerprint identification accuracy deteriorates
Solution Approach 1:
The patent changes the parameter of feature extraction by using intensity variation values instead of traditional fingerprint image features. This parameter change enables accurate identification with minimal sensing area, resolving the contradiction between area minimization and accuracy maintenance.
Solution Approach 2:
The patent performs preliminary noise filtering by applying artificial distortion to feature point candidate regions before final feature selection. This preliminary action ensures that even minimal sensing areas produce accurate identification results by eliminating noise early in the processing chain.
3Productivity
If traditional fingerprint processing methods are used with small sensing area, then device miniaturization is achieved, but feature information sufficiency deteriorates
Solution Approach 1:
The patent replaces traditional mechanical fingerprint image acquisition methods with an intelligent processing approach that extracts intensity variation values. This substitution enables sufficient feature information extraction from minimal sensing areas, achieving device miniaturization without information loss.
Solution Approach 2:
The patent introduces intensity variation values as an intermediary representation between the raw fingerprint image and the final identification result. This intermediary enables sufficient feature information to be obtained from small sensing areas by focusing on essential variation patterns rather than complete image data.
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 method enables the extraction of sufficient feature information from a small fingerprint sensing area, improving identification accuracy and reducing the necessary sensing area, thus enhancing user convenience and minimizing non-display regions in devices.
Implementation Method 1
the fingerprint recognition sensor by the capacitive method acquires a shape of a fingerprint (a fingerprint pattern) by detecting variations of capacitance according to shapes of ridges and valleys of a fingerprint
Data Source
AI summary
According to one embodiment, provided is a method by which an electronic device comprising a minimum fingerprint sensing area processes fingerprint information, comprising the steps of: acquiring a fingerprint image from the fingerprint sensing area; calculating a shade change value, defined by a shade difference value from a neighboring pixel, for each pixel of the fingerprint image; selecting points, as feature point candidates, of which the shade change value is a threshold value or more; applying artificial distortion for noise filtering to an area including the feature point candidates and neighboring pixels thereof; and selecting, as final feature points, candidates of which the shade change value after the artificial distortion is within a threshold range from among the feature point candidates.