Optical Material Detector Using Distance-Decoupled Reflection Imaging
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Solution Overview
Problem
Existing material identification methods struggle with reliable classification and identification due to features that depend on distance and material, particularly in reflective modes, leading to inaccurate results, especially with translucent materials.
Innovation Solution
A detector system utilizing a matrix of optical sensors with distance and material-dependent image filters to analyze reflection images, determining distance and material features through depth-from-photon-ratio and depth-from-defocus filters, enabling accurate material property identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If material identification is performed using beam profile analysis with image filters, then material classification can be achieved, but the features depend on both distance and material properties making reliable identification impossible
Solution Approach 1:
The evaluation device separates the combined distance-material features into two independent components: distance features (determined by depth-from-photon-ratio filter and depth-from-defocus filter) and material features (determined by material-dependent image filters). This segmentation allows independent analysis of each parameter, eliminating the information loss caused by their entanglement in traditional beam profile analysis.
Solution Approach 2:
The patent introduces depth-from-photon-ratio and depth-from-defocus filters as intermediary tools that specifically extract distance information from the reflection image. These intermediary filters act as mediators between the raw beam profile data and the final material identification, isolating the distance component so that material features can be accurately determined without distance interference.
2Ease of operation
If reflective mode is used for material identification, then non-contact measurement is achieved, but wavelengths larger than 1000 nm are necessary to yield reliable results increasing device complexity
Solution Approach 1:
The patent changes the parameter of light wavelength from the conventional requirement of >1000 nm to the visible range of 400-780 nm. This parameter change is achieved by using material-dependent image filters that can extract material features from visible light reflection profiles, eliminating the need for complex infrared or longer wavelength systems while maintaining non-contact measurement capability.
3Measurement precision
If through beam mode is used for material classification, then reliable material identification can be achieved, but the method requires transmitting light through the sample which limits applicability to translucent and transparent materials only
Solution Approach 1:
Instead of transmitting light through the sample as in through-beam mode, the patent inverts the approach by analyzing the reflection of light from the material surface and subsurface. The evaluation device processes reflection images to extract material features, enabling reliable material identification for opaque, translucent, and transparent materials without requiring light transmission through the entire sample.
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 and efficient material property identification with low technical effort and resource requirements, effectively distinguishing between various materials including biological and non-biological tissues, and surfaces.
Implementation Method 1
recording at least one reflection image of a light beam originating from at least one object
Implementation Method 2
determining at least one distance feature φ1z by applying at least one distance dependent image filter φ1 to the reflection image, wherein the distance dependent image filter is at least one filter selected from the group consisting of: a depth-from-photon-ratio filter
Implementation Method 3
a depth-from-defocus filter
Implementation Method 4
determining at least one material feature φ2m by applying at least one material dependent image filter φ2 to the reflection image
Data Source
AI summary
Described herein are systems including a structured light projector, a semiconductor detector, and a processor. Also described herein is a non-transitory computer readable medium storing executable instructions. The systems and non-transitory computer readable medium are configured to output a signal including information related to the classification of an object.