Biometric Authentication Illumination Estimation
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Solution Overview
Problem
Conventional biometric identification devices struggle to differentiate between real and fake biometric features, such as distinguishing between a real human face and artificial copies, limiting their verification capabilities.
Innovation Solution
An apparatus and method that detect a first biometric feature and a second biometric feature based on image data, where the second feature differs from the first, and estimate an illumination indication to discriminate between real and fake biometric features, using circuitry with processors, sensors, and machine learning algorithms to analyze image data and generate a skin map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional biometric identification devices use simple pattern recognition, then the device complexity is low, but the reliability of distinguishing real from fake biometric features deteriorates
Solution Approach 1:
The verification process is segmented into multiple independent detection stages: first biometric feature detection, second biometric feature detection from image data, and illumination indication estimation. Each stage processes different aspects of the biometric data, allowing the system to achieve high reliability through cumulative verification rather than relying on a single complex algorithm.
Solution Approach 2:
Illumination indication estimation serves as an intermediary parameter that mediates between the raw image data and the final authentication decision. By analyzing illumination characteristics separately and using them to adjust or validate the biometric feature extraction, the system adds a verification layer without requiring complete redesign of the core recognition algorithms.
2Reliability
If multiple biometric features are detected using different methods, then the reliability of biometric identification is improved, but the device complexity increases
Solution Approach 1:
The circuitry is designed with multi-functionality to perform both first biometric feature detection and second biometric feature detection from image data using the same hardware platform. This universal detection system reduces device complexity compared to having separate specialized devices for each detection method, while still achieving improved authentication reliability through the combination of multiple detection approaches.
3Reliability
If illumination indication estimation is performed based on image data, then the ability to discriminate real from fake biometric features is improved, but the measurement precision requirements increase
Solution Approach 1:
The illumination indication estimation performs partial analysis of the image data, focusing specifically on illumination characteristics rather than attempting complete scene reconstruction or perfect color accuracy. This partial action approach provides sufficient discrimination capability for detecting fake biometric features without requiring the excessive measurement precision that would be needed for complete image fidelity.
Data Source
AI summary
An apparatus has a circuitry which detects a first biometric feature of a user; detects a second biometric feature of the user, wherein the second biometric feature is detected based on image data representing the second biometric feature, and wherein the second biometric feature differs from the first biometric feature; and estimates an illumination indication for the second biometric feature, based on the image data.