Multispectral Wavelength Selection for Accurate Material Discrimination
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing hyperspectral cameras and foreign matter contamination examination devices struggle to efficiently identify specific wavelengths for accurate detection of objects due to the complexity of spectral data from multiple wavelengths, making it difficult to discriminate between different materials.
Innovation Solution
A data processing apparatus and method that calculates intensity characteristics at selected wavelengths using expressions for intensity difference and ratio, converts these into discrimination data, and outputs suitable wavelength combinations for detection, utilizing a multispectral camera with bandpass filters to enhance discrimination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectral data from many wavelengths is measured, then sensing capability is improved, but data complexity and difficulty of identifying specific wavelengths increases
Solution Approach 1:
The patent extracts only the necessary wavelength information from the full spectral data by calculating intensity characteristics at specific wavelengths and converting them into discrimination data. This extraction process isolates the critical detection information from the overwhelming full-spectrum data, enabling efficient identification of specific wavelengths suitable for detecting the target object while discarding redundant information.
Solution Approach 2:
The patent performs preliminary calculation of intensity characteristics and conversion to discrimination data before final detection. By pre-processing the spectral data to identify promising wavelength combinations through intensity difference and ratio calculations, the system prepares the data in advance for more efficient target detection, reducing the complexity of the subsequent detection process.
2Measurement precision
If spectral data from many wavelengths is measured, then sensing capability is improved, but ease of identifying specific wavelengths deteriorates
Solution Approach 1:
The patent extracts only the necessary wavelength information from the full spectral data by calculating intensity characteristics at specific wavelengths and converting them into discrimination data. This extraction process isolates the critical detection information from the overwhelming full-spectrum data, enabling efficient identification of specific wavelengths suitable for detecting the target object while discarding redundant information.
Solution Approach 2:
The patent transforms the raw spectral data into a different parameter space by calculating intensity characteristics (intensity difference and intensity ratio) at selected wavelengths. This parameter transformation converts complex spectral information into more manageable discrimination data that is easier to analyze and interpret, simplifying the process of identifying suitable wavelengths for detection.
3Measurement precision
If intensity characteristics are calculated at multiple wavelengths, then discrimination accuracy is improved, but calculation complexity increases
Solution Approach 1:
The patent transforms the raw spectral data into a different parameter space by calculating intensity characteristics (intensity difference and intensity ratio) at selected wavelengths. This parameter transformation converts complex spectral information into more manageable discrimination data that is easier to analyze and interpret, simplifying the process of identifying suitable wavelengths for detection.
Solution Approach 2:
The patent calculates intensity characteristics at a selected subset of wavelengths rather than processing all available spectral data. By focusing calculations on specific wavelengths that are most relevant for discrimination, the system achieves adequate discrimination accuracy with reduced computational effort, avoiding the excessive complexity that would result from processing the entire spectrum.
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
Enables accurate and efficient detection of specific objects by identifying optimal wavelength combinations, improving discrimination between materials and enhancing sensing performance.
Implementation Method 1
utilizing a multispectral camera with bandpass filters to enhance discrimination
Data Source
AI summary
A data processing apparatus includes a processor, in which the processor executes data acquisition processing of acquiring spectral data of a plurality of subjects, calculation processing of calculating intensity characteristics at a first wavelength and a second wavelength selected from wavelength ranges of the acquired spectral data of the plurality of subjects based on a relationship between two wavelengths which are the first wavelength and the second wavelength, data conversion processing of converting the intensity characteristics calculated in the calculation processing into discrimination data of a specific subject for the wavelength range, and output processing of outputting the discrimination data to an outside.