Skin Reflectance Image Correction for Biometric Capture
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Solution Overview
Problem
Biometric image capture systems face challenges in accurately quantifying phenotypes, particularly skin reflectance, which affects the performance of biometric matching, as existing methods struggle to consistently capture images within acceptable reflectance ranges, leading to inefficiencies and inaccuracies in identification processes.
Innovation Solution
A system and method that utilize a processing system with a hardware processor to calculate and adjust image capture settings based on relative skin reflectance values, ensuring that captured images fall within predetermined thresholds by remedying capture settings to achieve suitable reflectance for biometric matching, involving image processing logic to derive and adjust reflectance values and capture parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image capture settings are adjusted to improve skin reflectance values, then biometric matching accuracy is improved, but capture time and system complexity increase
Solution Approach 1:
The system performs preliminary analysis of the first captured image to determine if skin reflectance values are within the acceptable range before proceeding to biometric matching. This preliminary check prevents wasting time on images that will ultimately be rejected, allowing the system to quickly identify and recapture only those images that fail the reflectance criteria.
Solution Approach 2:
The system implements a feedback mechanism where the skin reflectance analysis results from the first image capture are used to adjust capture settings or trigger a second capture. The feedback loop continuously monitors reflectance values and adjusts the capture process accordingly, improving measurement accuracy while managing capture time through iterative refinement.
2Reliability
If multiple images are captured to ensure suitable reflectance values, then biometric matching reliability is improved, but processing time increases
Solution Approach 1:
The system performs preliminary skin reflectance analysis on captured images before committing to full biometric matching processing. By pre-screening images for acceptable reflectance values, the system ensures that only suitable images proceed to detailed matching, thereby improving reliability without unnecessarily slowing down the overall identification process for images that meet criteria on first capture.
Solution Approach 2:
The system performs a partial analysis (skin reflectance check) on all captured images before performing the complete biometric matching process. This partial action filters out unsuitable images early, allowing the system to maintain high reliability for matched images while avoiding excessive processing time for images that would fail reflectance criteria anyway.
3Manufacturing precision
If skin reflectance values are corrected through multiple captures, then image quality is improved, but system complexity increases
Solution Approach 1:
The system implements preliminary skin reflectance analysis as a simple threshold-based filter before more complex biometric processing. This preliminary action uses straightforward comparisons against minimum and maximum reflectance values, maintaining low complexity while improving image quality by identifying candidates suitable for detailed matching.
Solution Approach 2:
The system uses feedback from reflectance analysis to control whether a second capture is initiated. The feedback mechanism compares measured reflectance values against acceptable ranges and triggers remedial capture settings only when necessary, thereby improving image quality through selective correction while keeping system complexity manageable through conditional rather than universal multi-capture sequences.
Data Source
AI summary
In examples, a relative skin reflectance of a captured image of a subject is quantified. Based on the relative skin reflectance, the captured image is determined as suitable or not suitable for biometric identification. When the captured image is determined not suitable, a remedial capture setting is calculated and provided to an image capturing resource. Another captured image of the subject, captured under the remedial capture setting, is received from the image capturing resource. The relative skin reflectance of the another captured image is quantified and based thereon, there is a determining of whether the another captured image is suitable or is not suitable.