Fingerprint Feature Triangles for High-Speed Identification
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Solution Overview
Problem
Conventional fingerprint identification systems face inefficiencies in large-scale applications due to the time-consuming direct comparison method, especially when dealing with numerous fingerprint feature files, leading to low identification speed and accuracy.
Innovation Solution
The system establishes multiple feature triangles based on geometric data from fingerprint feature points, classifies these triangles into predetermined classifications, and compares new feature triangles with stored triangles of the same classification, reducing identification time by using high-speed value-comparison processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If direct comparison method is used to compare scanned fingerprint with all stored fingerprint feature files, then the system framework remains simple, but identification time increases significantly and efficiency decreases
Solution Approach 1:
The patent segments the fingerprint comparison process into two distinct stages: feature extraction stage where geometric features (minutiae points, ridges, valleys) are extracted and transformed into numerical data, and comparison stage where only the numerical data is compared. This segmentation allows simple system architecture while dramatically improving efficiency by reducing the complexity of direct image comparison.
Solution Approach 2:
The patent extracts key geometric features from the fingerprint image and transforms them into numerical representations. Only these extracted numerical features are used for comparison, not the entire fingerprint image. This extraction approach simplifies the comparison process and reduces identification time while maintaining accuracy.
2Productivity
If additional specific features (Fingerprint Directions, Core Points, Delta Points) are retrieved and classified to enhance efficiency, then identification speed improves, but system framework becomes much more complex
Solution Approach 1:
The patent creates a universal feature extraction module that can extract multiple types of geometric features (minutiae points, ridges, valleys) and transform them into a standardized numerical format. This multi-functional approach allows the system to handle various fingerprint characteristics through a single unified process, improving speed without proportionally increasing complexity.
Solution Approach 2:
The patent transforms fingerprint features from their original complex image representations into simplified numerical parameters. By changing the representation format from pixel-based images to coordinate-based numerical data, the system achieves faster comparison while maintaining the essential identifying characteristics, thus improving speed without excessive complexity increase.
Data Source
AI summary
A fingerprint feature identification system and method utilizes multiple feature points on a fingerprint to build feature triangles. Each of the feature triangles are classified as one of predetermined triangle classifications according to geometric data thereof. Every new feature triangle built from a new fingerprint is classified first and then compared with its geometric data to multiple filed feature triangles with the same triangle classification to shorten overall comparison duration.