Fingerprint Image Contrast Normalization for Pressure Variation
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Solution Overview
Problem
Existing fingerprint recognition technologies face challenges in accurately processing images due to variations in finger pressure, leading to non-uniform brightness distributions and degraded authentication performance.
Innovation Solution
A method is proposed to generate a reference image reflecting the brightness change trend of an original fingerprint image, normalize the contrast distribution using a kernel function, and apply smoothing techniques to remove noise, thereby enhancing ridge extraction and image registration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fingerprint images are captured with varying finger pressure, then the authentication process can be completed, but the brightness distribution becomes non-uniform leading to degraded authentication performance
Solution Approach 1:
The patent applies histogram equalization to transform the brightness distribution of the fingerprint image. By changing the parameter distribution of pixel intensities through histogram equalization, the method converts non-uniform brightness caused by pressure variations into a uniform distribution, thereby improving authentication performance without requiring controlled pressure conditions
2Measurement precision
If traditional fingerprint processing methods are used, then the processing is simple, but ridge extraction and image registration accuracy are degraded due to non-uniform contrast
Solution Approach 1:
The patent performs histogram equalization as a preliminary processing step before ridge extraction and image registration. By pre-processing the fingerprint image to achieve uniform brightness distribution, the method improves the accuracy of subsequent ridge extraction and registration operations without adding complex real-time processing requirements
Data Source
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AI summary
A method of processing a fingerprint image in an electronic apparatus includes: obtaining an original fingerprint image by sensing a fingerprint of a user; estimating a spatial change trend of original contrast values in the original fingerprint image; generating a reference contrast map based on the estimated spatial change trend; normalizing a contrast distribution of the original fingerprint image based on the reference contrast map, and generating a normalization fingerprint image having a normalized contrast distribution.