Fingerprint Verification Using Radon Transform Partial Regions
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Solution Overview
Problem
The accuracy of feature point-based fingerprint verification methods decreases when the number of feature points extracted from a fingerprint image is small or the image quality is low, and these methods have a high false recognition rate due to not considering regions adjacent to feature points.
Innovation Solution
The proposed method improves fingerprint verification accuracy by using a Radon transform to obtain feature information from partial regions surrounding the feature points, which are then verified using variance vectors stored in a database, allowing for more accurate matching and reduced false recognition rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If feature point-based verification is used, then verification speed is improved, but accuracy decreases when the number of feature points is small or image quality is low
Solution Approach 1:
The patent combines feature point-based verification with partial region-based verification by integrating both methods into a unified verification process. The system extracts feature points for rapid matching and simultaneously analyzes partial regions surrounding these feature points, merging the speed advantage of feature point methods with the accuracy advantage of region-based methods to resolve the contradiction between verification speed and accuracy.
Solution Approach 2:
The patent segments the fingerprint image into multiple partial regions centered around extracted feature points. By dividing the verification process into multiple regional analyses rather than treating the entire image as one unit, the system can focus computational resources on critical areas, improving accuracy without sacrificing the speed benefits of feature point-based approaches.
2Device complexity
If only feature points are used for verification, then device complexity is reduced, but false recognition rate increases
Solution Approach 1:
The patent transitions from one-dimensional feature point coordinates to two-dimensional partial region analysis by examining the spatial distribution and patterns of ridge structures within regions surrounding feature points. This dimensional expansion adds contextual information without significantly increasing device complexity, thereby reducing false recognition rates while maintaining system simplicity.
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 accuracy of fingerprint verification by considering regional features, improving the reliability of the verification process even with smaller or lower-quality fingerprint images, while maintaining the advantages of feature point-based methods.
Implementation Method 1
performing a Radon transform on the at least one partial region, and obtaining the partial region feature information based on a result of the Radon transform
Data Source
AI summary
A method of verifying a fingerprint includes selecting a feature point from among feature points of a fingerprint image, the selected feature point matching a registered feature point; determining a partial region of the fingerprint corresponding to the feature point in the fingerprint image; obtaining feature information of the partial region of the fingerprint in the fingerprint image; and verifying the fingerprint based on the feature information of the partial region in the fingerprint image.