3D Friction Ridge Imaging via Dynamic Compression Sequences
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Solution Overview
Problem
Current fingerprint imaging technologies fail to capture variations in elevation of friction ridges, leading to flattened representations and inadequate discrimination power, especially with Level III features showing significant variability under different conditions.
Innovation Solution
A system and method that capture a sequence of images using various imaging systems, such as TIR or ultrasound scanners, to extract three-dimensional topographical information, aggregating these images to create a representation of friction ridge patterns that depict changes in elevation and topography, enabling the identification of Level III features like ridge peaks, notches, and pores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional two-dimensional fingerprint imaging is used to capture friction ridge patterns, then the imaging process is simple and fast, but the elevation variations of friction ridges are lost and discrimination power is insufficient
Solution Approach 1:
The patent transitions from two-dimensional fingerprint imaging to three-dimensional topographical mapping by capturing sequences of images at different compression levels. This dimensional change enables the visualization of elevation variations (Level III features) such as ridge peaks, valleys, and notches that are invisible in traditional flat fingerprints, thereby significantly improving discrimination power without requiring fundamentally new imaging hardware
Solution Approach 2:
The system performs preliminary compression of the friction ridge pattern at multiple controlled levels before final image capture. By pre-compressing the ridges to different degrees and capturing images at each stage, the system builds a temporal sequence that can be aggregated into a three-dimensional representation, allowing elevation information to be extracted from otherwise redundant sequential images
2Loss of information
If multiple images are captured in slap fingerprint methods, then more data is collected, but only a single frame is used for identification and other images are discarded as poor captures
Solution Approach 1:
The patent merges multiple sequential images that were previously discarded as poor captures into a unified three-dimensional topographical representation. By aggregating information from all frames in the sequence and combining them according to temporal compression levels, the system transforms wasted redundant data into valuable elevation information, achieving complete utilization of captured images while maintaining efficient automated identification
Solution Approach 2:
The system uses temporal information from image sequences to provide feedback about compression levels and ridge contact states. This feedback mechanism allows the system to intelligently aggregate images by identifying which frames correspond to specific compression stages, enabling accurate reconstruction of three-dimensional topography while automatically filtering and combining only the most informative frames
3Measurement precision
If pressure is applied to ensure friction ridges are compressed against the imaging surface, then ridge lines are clearly visible, but variations in elevation are flattened and not visible
Solution Approach 1:
The patent applies dynamic compression by progressively increasing pressure on the friction ridge pattern over time and capturing images at multiple compression stages. Rather than using a single static high-pressure image that flattens all elevation variations, the system dynamically adjusts compression levels and captures the transition states, allowing three-dimensional topography to be reconstructed from the sequence of dynamically captured images
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 allows for more accurate identification of individuals by capturing detailed three-dimensional features of friction ridges, improving the discrimination power beyond traditional two-dimensional representations and reducing variability in feature recognition.
Implementation Method 1
total internal reflection based imaging systems (i.e., TIR imaging systems)
Implementation Method 2
ultrasound scanners
Data Source
AI summary
A representation of variations in elevation of friction ridges in a friction ridge pattern of a subject may be generated. A sequence of images captured over a time period may be obtained. Individual images in the sequence of images may indicate areas of engagement between an imaging surface and the friction ridge pattern of the subject when the individual images are captured. Temporal information may be obtained for the individual images. The temporal information for the individual images may be used to aggregate the individual images in the sequence of images into an aggregated representation of the friction ridge pattern. The aggregation may be accomplished such that the aggregated representation depicts the areas of engagement of the friction ridge pattern with the imaging surface at different elevations of the friction ridge pattern.