Hierarchical Fingerprint Image Merging System
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Solution Overview
Problem
Conventional methods for merging fingerprint images often result in errors and error propagation when the initial image is unclear, leading to suboptimal results in the enroll stage due to limitations in fingerprint sensor size and image merging algorithms.
Innovation Solution
A hierarchical structure is established with multiple levels, where each level includes a specific number of slices, allowing for the merging of fingerprint images across levels to create a complete enroll image, thereby reducing errors and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a conventional algorithm merges follow-up fingerprint images into the first fingerprint image, then the merging process is simple, but the merged fingerprint image may have many errors and cause error propagation when the first fingerprint image is not clear
Solution Approach 1:
The patent segments the merging process into multiple hierarchical levels. Instead of directly merging all images into one, it creates intermediate merging results at different levels (first level merging, second level merging, etc.), where each level processes a subset of images. This segmentation allows error isolation and prevents error propagation across the entire set of fingerprint images.
Solution Approach 2:
The patent implements a nested hierarchical structure where merging operations are organized in nested levels. The first level merges individual fingerprint images into intermediate results, the second level merges those intermediate results into higher-level results, and so on. This nesting allows the system to build up reliable merged images incrementally, with each level benefiting from the error-correcting properties of the previous levels.
2Measurement precision
If the fingerprint sensor area is made larger to capture complete fingerprint features in one scan, then the enroll stage accuracy improves, but the cost increases
Solution Approach 1:
The patent combines multiple smaller fingerprint images captured by a compact sensor into a single comprehensive merged fingerprint image. By using hierarchical merging algorithms that align and integrate features from multiple scans, the system achieves the feature completeness that would otherwise require a larger sensor area, thus avoiding increased device complexity and cost.
Solution Approach 2:
The patent transitions from a single-dimension approach (one large sensor capturing all features at once) to a multi-dimensional approach (multiple smaller sensors or repeated scans capturing different regions, then merged). This dimensional change allows the system to achieve complete fingerprint coverage through temporal and spatial multiplication rather than through a single large sensor area.
3Reliability
If multiple fingerprint images are scanned to ensure complete feature capture, then the enroll stage reliability improves, but the time required for scanning increases
Solution Approach 1:
The patent performs preliminary alignment and feature extraction on individual fingerprint images before the merging process. By pre-processing each image to identify key features and establish coordinate transformations, the system reduces the computational complexity of the actual merging operation, enabling faster processing of multiple scanned images and reducing overall enroll time.
Solution Approach 2:
The patent creates intermediate copied representations of fingerprint images at different hierarchical levels during the merging process. These copied intermediate results allow the system to efficiently combine information from multiple scans without repeatedly processing the original large datasets, thus reducing computational time while maintaining complete feature capture.
Data Source
AI summary
The method includes: setting up a hierarchy structure, wherein the hierarchy structure includes more than 2 levels, each slice in a lowest level of the levels is a single fingerprint image generated by a fingerprint sensor, a slice in a second level of the levels includes at most M slices in a first level of the levels, the second level is one level higher than the first level, and M is a positive integer greater than 1; obtaining a new fingerprint image, adding the new fingerprint image into the lowest level, arid updating the hierarchy structure; and outputting an enroll fingerprint image according to a slice in a highest level.


