Ridge Map Formation for Embedded Fingerprint Verification
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Solution Overview
Problem
Conventional fingerprint recognition systems are computationally intensive, making them inefficient on stand-alone or embedded computing platforms and requiring significant processing resources, which limits their use in applications that cannot be supported by desktop systems.
Innovation Solution
A method for ridge map formation that identifies candidate image feature pixels, examines local image data to locate potential feature pixels, and extracts features by neighboring contiguous data elements, bypassing computationally intensive Fast Fourier Transform and ridge thinning processes, thereby improving processing efficiency and reducing resource requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Fast Fourier Transform and ridge thinning processes are used to generate ridge maps, then the accuracy of fingerprint verification is improved, but the processing time and computational resources increase significantly
Solution Approach 1:
The patent extracts only the essential ridge map formation operations from the conventional FFT and thinning process, isolating the core functionality needed for accurate fingerprint verification while eliminating computationally intensive steps. This extraction approach maintains verification accuracy by preserving the essential ridge detection capability while removing the time-consuming mathematical transformations.
Solution Approach 2:
The patent changes the computational parameters and algorithms used in ridge map formation, replacing the standard FFT-based approach with an alternative method that achieves similar or equivalent ridge detection accuracy but with significantly reduced computational complexity and processing time, making it suitable for embedded systems.
2Measurement precision
If Fast Fourier Transform and ridge thinning processes are used to generate ridge maps, then the accuracy of fingerprint verification is improved, but the processing power and resource requirements increase
Solution Approach 1:
The patent employs simpler, less computationally expensive algorithms that consume fewer processing resources and power, sacrificing the complexity of FFT-based methods in favor of more efficient approaches that achieve adequate accuracy for embedded fingerprint verification applications.
Solution Approach 2:
The patent modifies the computational parameters and algorithmic complexity to reduce processing power requirements while maintaining acceptable verification accuracy, enabling deployment on resource-constrained embedded platforms.
3Measurement precision
If conventional FFT and thinning methods are used for ridge map formation, then comprehensive feature extraction is achieved, but the system complexity increases
Solution Approach 1:
The patent extracts and retains only the necessary feature extraction operations from the conventional method, removing unnecessary computational steps and system components that contribute to complexity while preserving the essential capability to extract fingerprint features for verification.
Solution Approach 2:
The patent applies different processing approaches to different regions or aspects of the fingerprint image, using simplified methods where full complexity is unnecessary while maintaining comprehensive feature extraction in critical areas, thereby reducing overall system complexity.
Data Source
AI summary
Disclosed is an apparatus, method, and computer program product for ridge map formation. The method for processing an image data structure to extract a feature defined by a plurality of contiguous data elements includes identifying a set of candidate image feature pixels, the set including one or more pixels from the image data structure; examining local image data surrounding one or more pixels of the set of candidate image feature pixels to identify a set of potential image feature pixels with each of the potential image feature pixels having a characteristic consistent with being associated with the feature; and identifying the feature in the image data using the set of potential image feature pixels by locating one or more of the plurality of contiguous data elements neighboring one or more pixels of the set of potential image feature pixels. The computer program product includes instructions executable by a processing unit, and those instructions perform the feature extraction as described herein. The system is an apparatus for processing an image data structure to extract a feature defined by a plurality of contiguous data elements.