Multi-Wavelength Material Detection for Skin and Silicon Differentiation
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Solution Overview
Problem
Existing material detection technologies face challenges in reliably distinguishing between skin and non-skin objects, particularly with realistic 3D silicon masks, requiring improved methods for secure authentication and identification in various applications with low technical effort and cost.
Innovation Solution
A detector system utilizing a projector with an illumination pattern and a flood light source of different wavelengths, combined with a sensor element and evaluation device, to determine material properties by analyzing beam profiles and scene images, enhancing the differentiation between materials, including skin and silicon.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single wavelength beam profile analysis is used for material detection, then device complexity is low, but measurement precision is insufficient for distinguishing skin from silicon masks
Solution Approach 1:
The patent applies parameter changes by utilizing multiple wavelengths (first wavelength from projector, second wavelength from flood light source) to illuminate the object. Different materials exhibit distinct reflectance characteristics at different wavelengths, enabling the evaluation device to differentiate between skin and silicon masks by analyzing how each material reflects light at these varying wavelengths, thereby improving measurement precision without excessive complexity increase
Solution Approach 2:
The patent introduces another dimension by adding wavelength as an additional parameter for material detection. Instead of relying solely on spatial beam profile analysis, the system incorporates spectral information by combining reflections from multiple wavelengths, effectively moving from a single-dimensional to multi-dimensional analysis approach that enhances material differentiation capability
2Measurement precision
If multi-wavelength illumination is used to improve material differentiation, then measurement precision increases, but device complexity increases
Solution Approach 1:
The patent applies universality by designing the sensor element to simultaneously capture reflections from multiple wavelengths using a single broadband sensor. The sensor element functions as a multi-functional device that processes both the first wavelength illumination pattern and the second wavelength flood light reflections, reducing the need for separate detection systems for each wavelength and thereby limiting the increase in device complexity
Solution Approach 2:
The patent applies segmentation by separating the illumination sources into distinct wavelength components (projector for first wavelength, flood light source for second wavelength) while using a unified detection and evaluation system. This segmentation of illumination functions allows for targeted wavelength-specific material interaction while maintaining integrated processing, balancing complexity with performance
3Reliability
If beam profile analysis is used for material detection, then ease of operation is good, but reliability is insufficient for security applications
Solution Approach 1:
The patent introduces an evaluation device as an intermediary component that automatically processes the complex task of comparing multi-wavelength reflection patterns against reference data. This intermediary handles the computational complexity of reliability-enhancing analysis, allowing the system to maintain ease of operation for end users while achieving high reliability through sophisticated multi-parameter material detection
Solution Approach 2:
The patent applies feedback by implementing a detection system that compares measured reflection patterns at multiple wavelengths against stored reference characteristics of known materials (including skin and spoof materials). The evaluation device uses this feedback mechanism to continuously assess material authenticity, improving reliability by identifying deviations from expected patterns while maintaining operational simplicity through automated decision-making
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
The system provides reliable material detection with improved accuracy in distinguishing between skin and non-skin objects, effectively addressing spoofing attacks and increasing the reliability of authentication processes.
Implementation Method 1
at least one projector for illuminating at least one object with at least one illumination pattern, wherein the illumination pattern comprises a plurality of illumination features, wherein the illumination features have a first wavelength
Implementation Method 2
at least one flood light source configured for scene illumination, wherein the flood light source is configured for emitting the scene illumination having a second wavelength different from the first wavelength
Implementation Method 3
at least one sensor element having a matrix of optical sensors, the optical sensors each having a light-sensitive area, wherein each optical sensor is designed to generate at least one sensor signal in response to an illumination of its respective light-sensitive area by a light beam propagating from the object to the detector
Implementation Method 4
The sensor element is configured for imaging at least one reflection image comprising a plurality of reflection features generated by the object in response to the illumination pattern
Data Source
AI summary
A detector for material detection of at least one object is disclosed. The detector includes:at least one projector for illuminating at least one object with at least one illumination pattern;at least one flood light source configured for scene illumination;at least one sensor element having a matrix of optical sensors,andat least one evaluation device.